{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/rebeccalittman/Documents/PK2 share/Replication/Data/ReplicationResults.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res}17 Dec 2015, 10:44:51

{com}. do "/var/folders/fx/_rgnnlgd33v9nxc17h3wwtvm0000gn/T//SD45121.000000"
{txt}
{com}. ***************************************************
. * Title: Pov_Viol Paper Data Analysis                          
. * Date: November 7, 2015                              
. ***************************************************
. 
{txt}end of do-file

{com}. do "/var/folders/fx/_rgnnlgd33v9nxc17h3wwtvm0000gn/T//SD45121.000000"
{txt}
{com}. *****************************************************
. ****************** PAPER ANALYSES *******************
. *****************************************************
. 
. set more off
{txt}
{com}. 
. // RELATIVE POVERTY MANIPULATION
. 
.         tab income poverty, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

           {c |}        poverty
    income {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         1 {c |}{res}       335      3,015 {txt}{c |}{res}     3,350 
           {txt}{c |}{res}      4.40      39.28 {txt}{c |}{res}     21.91 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         2 {c |}{res}       382      3,009 {txt}{c |}{res}     3,391 
           {txt}{c |}{res}      5.02      39.21 {txt}{c |}{res}     22.18 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         3 {c |}{res}     1,470        976 {txt}{c |}{res}     2,446 
           {txt}{c |}{res}     19.30      12.72 {txt}{c |}{res}     16.00 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         4 {c |}{res}     1,893        355 {txt}{c |}{res}     2,248 
           {txt}{c |}{res}     24.86       4.63 {txt}{c |}{res}     14.70 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         5 {c |}{res}     2,197        211 {txt}{c |}{res}     2,408 
           {txt}{c |}{res}     28.85       2.75 {txt}{c |}{res}     15.75 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         6 {c |}{res}     1,339        109 {txt}{c |}{res}     1,448 
           {txt}{c |}{res}     17.58       1.42 {txt}{c |}{res}      9.47 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}     7,616      7,675 {txt}{c |}{res}    15,291 
           {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}
{com}.         tab income_bottom poverty, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

income_bot {c |}        poverty
       tom {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}     7,281      4,660 {txt}{c |}{res}    11,941 
           {txt}{c |}{res}     95.60      60.72 {txt}{c |}{res}     78.09 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         1 {c |}{res}       335      3,015 {txt}{c |}{res}     3,350 
           {txt}{c |}{res}      4.40      39.28 {txt}{c |}{res}     21.91 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}     7,616      7,675 {txt}{c |}{res}    15,291 
           {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}
{com}.         reg income_bottom poverty, cluster (psu_new)

{txt}Linear regression                                      Number of obs ={res}   15259
                                                       {txt}F(  1,  1250) ={res}  693.51
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.1776
                                                       {txt}Root MSE      = {res} .37504

{txt}{ralign 78:(Std. Err. adjusted for {res:1251} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}income_bot~m{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}poverty {c |}{col 14}{res}{space 2} .3485717{col 26}{space 2} .0132363{col 37}{space 1}   26.33{col 46}{space 3}0.000{col 54}{space 4} .3226039{col 67}{space 3} .3745394
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .0440616{col 26}{space 2} .0059505{col 37}{space 1}    7.40{col 46}{space 3}0.000{col 54}{space 4} .0323875{col 67}{space 3} .0557356
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         bys poverty: summ d140, detail

{txt}{hline}
-> poverty = 0

             Cash family spent last month (D140)
{hline 61}
      Percentiles      Smallest
 1%    {res}     2000              0
{txt} 5%    {res}     5000              0
{txt}10%    {res}     7000              0       {txt}Obs         {res}       7542
{txt}25%    {res}    10000              0       {txt}Sum of Wgt. {res}       7542

{txt}50%    {res}    15000                      {txt}Mean          {res} 16373.63
                        {txt}Largest       Std. Dev.     {res} 9565.406
{txt}75%    {res}    20000          80000
{txt}90%    {res}    30000          85000       {txt}Variance      {res} 9.15e+07
{txt}95%    {res}    35000          85000       {txt}Skewness      {res} 1.885928
{txt}99%    {res}    50000          90000       {txt}Kurtosis      {res} 9.531249

{txt}{hline}
-> poverty = 1

             Cash family spent last month (D140)
{hline 61}
      Percentiles      Smallest
 1%    {res}     1500              0
{txt} 5%    {res}     5000            200
{txt}10%    {res}     7000            200       {txt}Obs         {res}       7553
{txt}25%    {res}    10000            300       {txt}Sum of Wgt. {res}       7553

{txt}50%    {res}    15000                      {txt}Mean          {res} 16576.82
                        {txt}Largest       Std. Dev.     {res} 9866.256
{txt}75%    {res}    20000          90000
{txt}90%    {res}    30000          90000       {txt}Variance      {res} 9.73e+07
{txt}95%    {res}    35000          90000       {txt}Skewness      {res}  1.83455
{txt}99%    {res}    50000          90000       {txt}Kurtosis      {res} 8.974036

{txt}{hline}
-> poverty = .

             Cash family spent last month (D140)
{hline 61}
      Percentiles      Smallest
 1%    {res}     5000           5000
{txt} 5%    {res}     5000           5000
{txt}10%    {res}     5000           8000       {txt}Obs         {res}         17
{txt}25%    {res}     9000           9000       {txt}Sum of Wgt. {res}         17

{txt}50%    {res}    10500                      {txt}Mean          {res} 12852.94
                        {txt}Largest       Std. Dev.     {res} 6323.974
{txt}75%    {res}    15000          18000
{txt}90%    {res}    20000          20000       {txt}Variance      {res} 4.00e+07
{txt}95%    {res}    30000          20000       {txt}Skewness      {res} 1.183646
{txt}99%    {res}    30000          30000       {txt}Kurtosis      {res} 4.203542

{txt}
{com}.         reg d140 poverty, cluster(psu_new)

{txt}Linear regression                                      Number of obs ={res}   15065
                                                       {txt}F(  1,  1246) ={res}    0.38
                                                       {txt}Prob > F      = {res} 0.5392
                                                       {txt}R-squared     = {res} 0.0001
                                                       {txt}Root MSE      = {res} 9721.9

{txt}{ralign 78:(Std. Err. adjusted for {res:1247} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}        d140{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}poverty {c |}{col 14}{res}{space 2} 206.7576{col 26}{space 2} 336.6525{col 37}{space 1}    0.61{col 46}{space 3}0.539{col 54}{space 4}-453.7108{col 67}{space 3} 867.2259
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 16376.35{col 26}{space 2} 233.7551{col 37}{space 1}   70.06{col 46}{space 3}0.000{col 54}{space 4} 15917.75{col 67}{space 3} 16834.94
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. // OVERALL ENDORSEMENT EFFECTS (FIGURE 1A)
. 
.         matrix results = J(5,2,0)
{txt}
{com}. 
.         local group  "b c d militancy e"
{txt}
{com}.         local a = 1
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x', cluster(psu_new)
{txt}  3{com}.                 mat results[`a',1] = _b[treat_`x']
{txt}  4{com}.                 mat results[`a',2] = _se[treat_`x']
{txt}  5{com}.                 local ++a
{txt}  6{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F(  1,   474) ={res}    0.02
                                                       {txt}Prob > F      = {res} 0.8972
                                                       {txt}R-squared     = {res} 0.0000
                                                       {txt}Root MSE      = {res} .24495

{txt}{ralign 78:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~b{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_b {c |}{col 14}{res}{space 2}-.0023256{col 26}{space 2} .0179891{col 37}{space 1}   -0.13{col 46}{space 3}0.897{col 54}{space 4}-.0376738{col 67}{space 3} .0330225
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6378284{col 26}{space 2} .0118784{col 37}{space 1}   53.70{col 46}{space 3}0.000{col 54}{space 4} .6144876{col 67}{space 3} .6611693
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F(  1,   475) ={res}    0.27
                                                       {txt}Prob > F      = {res} 0.6068
                                                       {txt}R-squared     = {res} 0.0004
                                                       {txt}Root MSE      = {res} .24526

{txt}{ralign 78:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~c{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_c {c |}{col 14}{res}{space 2}-.0094385{col 26}{space 2} .0183262{col 37}{space 1}   -0.52{col 46}{space 3}0.607{col 54}{space 4} -.045449{col 67}{space 3} .0265721
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6378284{col 26}{space 2} .0118784{col 37}{space 1}   53.70{col 46}{space 3}0.000{col 54}{space 4} .6144878{col 67}{space 3} .6611691
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F(  1,   483) ={res}    1.10
                                                       {txt}Prob > F      = {res} 0.2945
                                                       {txt}R-squared     = {res} 0.0015
                                                       {txt}Root MSE      = {res} .25366

{txt}{ralign 78:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~d{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_d {c |}{col 14}{res}{space 2}-.0199478{col 26}{space 2} .0190098{col 37}{space 1}   -1.05{col 46}{space 3}0.295{col 54}{space 4}-.0572998{col 67}{space 3} .0174043
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6378284{col 26}{space 2} .0118782{col 37}{space 1}   53.70{col 46}{space 3}0.000{col 54}{space 4} .6144891{col 67}{space 3} .6611678
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  1,   952) ={res}    0.53
                                                       {txt}Prob > F      = {res} 0.4667
                                                       {txt}R-squared     = {res} 0.0003
                                                       {txt}Root MSE      = {res} .25508

{txt}{ralign 81:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}policy_pref_m~y{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
treat_militancy {c |}{col 17}{res}{space 2}-.0104824{col 29}{space 2} .0143948{col 40}{space 1}   -0.73{col 49}{space 3}0.467{col 57}{space 4}-.0387316{col 70}{space 3} .0177667
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .6378284{col 29}{space 2} .0118716{col 40}{space 1}   53.73{col 49}{space 3}0.000{col 57}{space 4}  .614531{col 70}{space 3} .6611259
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F(  1,   490) ={res}    1.05
                                                       {txt}Prob > F      = {res} 0.3060
                                                       {txt}R-squared     = {res} 0.0013
                                                       {txt}Root MSE      = {res} .23655

{txt}{ralign 78:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_e {c |}{col 14}{res}{space 2} .0173079{col 26}{space 2} .0168909{col 37}{space 1}    1.02{col 46}{space 3}0.306{col 54}{space 4}-.0158796{col 67}{space 3} .0504954
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6378284{col 26}{space 2}  .011878{col 37}{space 1}   53.70{col 46}{space 3}0.000{col 54}{space 4} .6144904{col 67}{space 3} .6611665
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         matrix list results 
{res}
{txt}results[5,2]
            c1          c2
r1 {res} -.00232563   .01798905
{txt}r2 {res} -.00943845   .01832625
{txt}r3 {res} -.01994778   .01900976
{txt}r4 {res} -.01048241   .01439477
{txt}r5 {res}  .01730792    .0168909
{reset}
{com}. 
. 
. // KNOWLEDGE DIAGNOSTIC CHECK (FIGURE 1A) 
. 
.         matrix results = J(8,2,0)
{txt}
{com}. 
.         local a = 1
{txt}
{com}.         local b = 5
{txt}
{com}.         local group  "b c d militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' knowledgehigh know_treat_`x', cluster(psu_new) 
{txt}  3{com}.                 mat results[`a',1] = _b[treat_`x']
{txt}  4{com}.                 mat results[`a',2] = _se[treat_`x']
{txt}  5{com}.                 lincom treat_`x' + know_treat_`x'
{txt}  6{com}.                 mat results[`b',1] = r(estimate)
{txt}  7{com}.                 mat results[`b',2] = r(se)
{txt}  8{com}.                 local ++a
{txt}  9{com}.                 local ++b
{txt} 10{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F(  3,   474) ={res}    0.92
                                                       {txt}Prob > F      = {res} 0.4300
                                                       {txt}R-squared     = {res} 0.0017
                                                       {txt}Root MSE      = {res} .24479

{txt}{ralign 79:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}policy_pref_b{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}treat_b {c |}{col 15}{res}{space 2}  .007459{col 27}{space 2} .0184766{col 38}{space 1}    0.40{col 47}{space 3}0.687{col 55}{space 4}-.0288471{col 68}{space 3} .0437651
{txt}knowledgehigh {c |}{col 15}{res}{space 2} .0277085{col 27}{space 2} .0169377{col 38}{space 1}    1.64{col 47}{space 3}0.103{col 55}{space 4}-.0055737{col 68}{space 3} .0609908
{txt}{space 1}know_treat_b {c |}{col 15}{res}{space 2}-.0223691{col 27}{space 2} .0263227{col 38}{space 1}   -0.85{col 47}{space 3}0.396{col 55}{space 4}-.0740927{col 68}{space 3} .0293544
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .6254725{col 27}{space 2} .0119684{col 38}{space 1}   52.26{col 47}{space 3}0.000{col 55}{space 4} .6019549{col 68}{space 3} .6489901
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_b + know_treat_b = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~b{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0149102{col 26}{space 2} .0258971{col 37}{space 1}   -0.58{col 46}{space 3}0.565{col 54}{space 4}-.0657974{col 67}{space 3} .0359771
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F(  3,   475) ={res}    1.16
                                                       {txt}Prob > F      = {res} 0.3238
                                                       {txt}R-squared     = {res} 0.0024
                                                       {txt}Root MSE      = {res} .24505

{txt}{ralign 79:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}policy_pref_c{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}treat_c {c |}{col 15}{res}{space 2}-.0042452{col 27}{space 2} .0187095{col 38}{space 1}   -0.23{col 47}{space 3}0.821{col 55}{space 4}-.0410088{col 68}{space 3} .0325183
{txt}knowledgehigh {c |}{col 15}{res}{space 2} .0277085{col 27}{space 2} .0169377{col 38}{space 1}    1.64{col 47}{space 3}0.103{col 55}{space 4}-.0055736{col 68}{space 3} .0609906
{txt}{space 1}know_treat_c {c |}{col 15}{res}{space 2}-.0126225{col 27}{space 2} .0250706{col 38}{space 1}   -0.50{col 47}{space 3}0.615{col 55}{space 4}-.0618854{col 68}{space 3} .0366405
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .6254725{col 27}{space 2} .0119684{col 38}{space 1}   52.26{col 47}{space 3}0.000{col 55}{space 4}  .601955{col 68}{space 3}   .64899
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_c + know_treat_c = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~c{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0168677{col 26}{space 2} .0255758{col 37}{space 1}   -0.66{col 46}{space 3}0.510{col 54}{space 4}-.0671234{col 67}{space 3}  .033388
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F(  3,   483) ={res}    1.43
                                                       {txt}Prob > F      = {res} 0.2334
                                                       {txt}R-squared     = {res} 0.0038
                                                       {txt}Root MSE      = {res} .25342

{txt}{ralign 79:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 14}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 15}{c |}{col 27}    Robust
{col 1}policy_pref_d{col 15}{c |}      Coef.{col 27}   Std. Err.{col 39}      t{col 47}   P>|t|{col 55}     [95% Con{col 68}f. Interval]
{hline 14}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 6}treat_d {c |}{col 15}{res}{space 2}-.0171236{col 27}{space 2} .0204083{col 38}{space 1}   -0.84{col 47}{space 3}0.402{col 55}{space 4}-.0572236{col 68}{space 3} .0229763
{txt}knowledgehigh {c |}{col 15}{res}{space 2} .0277085{col 27}{space 2} .0169374{col 38}{space 1}    1.64{col 47}{space 3}0.103{col 55}{space 4}-.0055716{col 68}{space 3} .0609887
{txt}{space 1}know_treat_d {c |}{col 15}{res}{space 2}-.0078846{col 27}{space 2} .0280501{col 38}{space 1}   -0.28{col 47}{space 3}0.779{col 55}{space 4}-.0629999{col 68}{space 3} .0472308
{txt}{space 8}_cons {c |}{col 15}{res}{space 2} .6254725{col 27}{space 2} .0119682{col 38}{space 1}   52.26{col 47}{space 3}0.000{col 55}{space 4} .6019563{col 68}{space 3} .6489887
{txt}{hline 14}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_d + know_treat_d = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~d{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0250082{col 26}{space 2} .0267523{col 37}{space 1}   -0.93{col 46}{space 3}0.350{col 54}{space 4}-.0775735{col 67}{space 3} .0275571
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}    1.41
                                                       {txt}Prob > F      = {res} 0.2385
                                                       {txt}R-squared     = {res} 0.0016
                                                       {txt}Root MSE      = {res} .25494

{txt}{ralign 86:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}policy_pref_milita~y{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      t{col 54}   P>|t|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_militancy {c |}{col 22}{res}{space 2}-.0045181{col 34}{space 2} .0147698{col 45}{space 1}   -0.31{col 54}{space 3}0.760{col 62}{space 4}-.0335031{col 75}{space 3}  .024467
{txt}{space 7}knowledgehigh {c |}{col 22}{res}{space 2} .0277085{col 34}{space 2} .0169264{col 45}{space 1}    1.64{col 54}{space 3}0.102{col 62}{space 4}-.0055088{col 75}{space 3} .0609258
{txt}know_treat_militancy {c |}{col 22}{res}{space 2}-.0143668{col 34}{space 2} .0206001{col 45}{space 1}   -0.70{col 54}{space 3}0.486{col 62}{space 4}-.0547936{col 75}{space 3} .0260599
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .6254725{col 34}{space 2} .0119604{col 45}{space 1}   52.30{col 54}{space 3}0.000{col 62}{space 4} .6020008{col 75}{space 3} .6489442
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + know_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0188849{col 26}{space 2}  .020547{col 37}{space 1}   -0.92{col 46}{space 3}0.358{col 54}{space 4}-.0592075{col 67}{space 3} .0214377
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         matrix list results     
{res}
{txt}results[8,2]
            c1          c2
r1 {res}  .00745896   .01847656
{txt}r2 {res} -.00424524   .01870947
{txt}r3 {res} -.01712363   .02040827
{txt}r4 {res} -.00451806   .01476975
{txt}r5 {res} -.01491016   .02589706
{txt}r6 {res} -.01686769   .02557581
{txt}r7 {res}  -.0250082   .02675233
{txt}r8 {res} -.01888489   .02054698
{reset}
{com}. 
. 
. // EDHI DIAGNOSTIC CHECK (FIGURE 1B)
. 
.         matrix results = J(2,2,0)
{txt}
{com}.         
.         reg policy_pref_e treat_e if q1001<3, cluster(psu_new)

{txt}Linear regression                                      Number of obs ={res}    3517
                                                       {txt}F(  1,   446) ={res}    3.05
                                                       {txt}Prob > F      = {res} 0.0813
                                                       {txt}R-squared     = {res} 0.0048
                                                       {txt}Root MSE      = {res} .22293

{txt}{ralign 78:(Std. Err. adjusted for {res:447} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_e {c |}{col 14}{res}{space 2} .0310418{col 26}{space 2} .0177652{col 37}{space 1}    1.75{col 46}{space 3}0.081{col 54}{space 4}-.0038722{col 67}{space 3} .0659558
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .670998{col 26}{space 2} .0126959{col 37}{space 1}   52.85{col 46}{space 3}0.000{col 54}{space 4} .6460468{col 67}{space 3} .6959492
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         mat results[1,1] = _b[treat_e]
{txt}
{com}.         mat results[1,2] = _se[treat_e]
{txt}
{com}. 
.         reg policy_pref_e treat_e if q1001>2 & q1001!=., cluster(psu_new)

{txt}Linear regression                                      Number of obs ={res}    1700
                                                       {txt}F(  1,   346) ={res}    0.02
                                                       {txt}Prob > F      = {res} 0.8764
                                                       {txt}R-squared     = {res} 0.0001
                                                       {txt}Root MSE      = {res} .24397

{txt}{ralign 78:(Std. Err. adjusted for {res:347} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_e {c |}{col 14}{res}{space 2}-.0041996{col 26}{space 2} .0269836{col 37}{space 1}   -0.16{col 46}{space 3}0.876{col 54}{space 4} -.057272{col 67}{space 3} .0488728
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5623457{col 26}{space 2} .0188709{col 37}{space 1}   29.80{col 46}{space 3}0.000{col 54}{space 4} .5252295{col 67}{space 3} .5994619
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         mat results[2,1] = _b[treat_e]
{txt}
{com}.         mat results[2,2] = _se[treat_e]
{txt}
{com}. 
.         matrix list results
{res}
{txt}results[2,2]
            c1          c2
r1 {res}  .03104181   .01776524
{txt}r2 {res} -.00419961   .02698355
{reset}
{com}. 
. 
. // OBSERVATIONAL POVERTY RESULTS (FIGURE 2)
. 
.         matrix results = J(4,2,0)
{txt}
{com}. 
.         local group  "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' lowexp20_urprov highexp20_urprov treat_`x' lowexp20_urprov_`x' highexp20_urprov_`x', cluster(psu_new)
{txt}  3{com}.                 mat results[1,1] = _b[treat_`x']
{txt}  4{com}.                 mat results[1,2] = _se[treat_`x']
{txt}  5{com}.                 lincom treat_`x' + lowexp20_urprov_`x'
{txt}  6{com}.                 mat results[2,1] = r(estimate)
{txt}  7{com}.                 mat results[2,2] = r(se)
{txt}  8{com}.                 lincom treat_`x' + highexp20_urprov_`x'
{txt}  9{com}.                 mat results[3,1] = r(estimate)
{txt} 10{com}.                 mat results[3,2] = r(se)
{txt} 11{com}.                 lincom lowexp20_urprov_`x' - highexp20_urprov_`x'
{txt} 12{com}.                 mat results[4,1] = r(estimate)
{txt} 13{com}.                 mat results[4,2] = r(se)
{txt} 14{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  5,   952) ={res}    6.77
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0106
                                                       {txt}Root MSE      = {res} .25381

{txt}{ralign 92:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}     policy_pref_militancy{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      t{col 60}   P>|t|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}lowexp20_urprov {c |}{col 28}{res}{space 2}-.0136784{col 40}{space 2} .0160782{col 51}{space 1}   -0.85{col 60}{space 3}0.395{col 68}{space 4}-.0452313{col 81}{space 3} .0178744
{txt}{space 10}highexp20_urprov {c |}{col 28}{res}{space 2} .0084175{col 40}{space 2} .0162252{col 51}{space 1}    0.52{col 60}{space 3}0.604{col 68}{space 4}-.0234238{col 81}{space 3} .0402588
{txt}{space 11}treat_militancy {c |}{col 28}{res}{space 2}-.0106003{col 40}{space 2} .0165208{col 51}{space 1}   -0.64{col 60}{space 3}0.521{col 68}{space 4}-.0430218{col 81}{space 3} .0218212
{txt}{space 1}lowexp20_urprov_militancy {c |}{col 28}{res}{space 2}-.0318086{col 40}{space 2} .0204949{col 51}{space 1}   -1.55{col 60}{space 3}0.121{col 68}{space 4} -.072029{col 81}{space 3} .0084118
{txt}highexp20_urprov_militancy {c |}{col 28}{res}{space 2} .0341845{col 40}{space 2} .0194241{col 51}{space 1}    1.76{col 60}{space 3}0.079{col 68}{space 4}-.0039346{col 81}{space 3} .0723036
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .6391102{col 40}{space 2} .0138908{col 51}{space 1}   46.01{col 60}{space 3}0.000{col 68}{space 4} .6118501{col 81}{space 3} .6663703
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + lowexp20_urprov_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0424089{col 26}{space 2} .0215816{col 37}{space 1}   -1.97{col 46}{space 3}0.050{col 54}{space 4}-.0847619{col 67}{space 3}-.0000559
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{p 0 7}{space 1}{text:( 1)}{space 1} {res}treat_militancy + highexp20_urprov_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0235842{col 26}{space 2} .0191086{col 37}{space 1}    1.23{col 46}{space 3}0.217{col 54}{space 4}-.0139156{col 67}{space 3}  .061084
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{p 0 7}{space 1}{text:( 1)}{space 1} {res}lowexp20_urprov_militancy - highexp20_urprov_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0659931{col 26}{space 2} .0262217{col 37}{space 1}   -2.52{col 46}{space 3}0.012{col 54}{space 4}-.1174521{col 67}{space 3} -.014534
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
.         matrix list results     
{res}
{txt}results[4,2]
            c1          c2
r1 {res} -.01060029   .01652084
{txt}r2 {res} -.04240888    .0215816
{txt}r3 {res}  .02358419   .01910858
{txt}r4 {res} -.06599307   .02622174
{reset}
{com}. 
. 
. // RESULTS OF THE RELATIVE POVERTY EXPERIMENT (FIGURE 2)
. 
.         matrix results = J(3,2,0)
{txt}
{com}.         
.         local group  "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x', cluster(psu_new) 
{txt}  3{com}.                 mat results[1,1] = _b[poverty_treat_`x']
{txt}  4{com}.                 mat results[1,2] = _se[poverty_treat_`x']
{txt}  5{com}.                 mat results[2,1] = _b[treat_`x']
{txt}  6{com}.                 mat results[2,2] = _se[treat_`x']
{txt}  7{com}.                 lincom treat_`x' + poverty_treat_`x'
{txt}  8{com}.                 mat results[3,1] = r(estimate)
{txt}  9{com}.                 mat results[3,2] = r(se)
{txt} 10{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}    1.32
                                                       {txt}Prob > F      = {res} 0.2678
                                                       {txt}R-squared     = {res} 0.0025
                                                       {txt}Root MSE      = {res} .25482

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0151704{col 37}{space 2} .0200743{col 48}{space 1}    0.76{col 57}{space 3}0.450{col 65}{space 4}-.0242247{col 78}{space 3} .0545654
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0312276{col 37}{space 2}  .023629{col 48}{space 1}    1.32{col 57}{space 3}0.187{col 65}{space 4}-.0151434{col 78}{space 3} .0775986
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0523725{col 37}{space 2} .0286912{col 48}{space 1}   -1.83{col 57}{space 3}0.068{col 65}{space 4}-.1086778{col 78}{space 3} .0039327
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .6226903{col 37}{space 2} .0167844{col 48}{space 1}   37.10{col 57}{space 3}0.000{col 65}{space 4} .5897515{col 78}{space 3} .6556291
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + poverty_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0372022{col 26}{space 2} .0204989{col 37}{space 1}   -1.81{col 46}{space 3}0.070{col 54}{space 4}-.0774304{col 67}{space 3}  .003026
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         matrix list results     
{res}
{txt}results[3,2]
            c1          c2
r1 {res} -.05237255   .02869115
{txt}r2 {res}  .01517035   .02007431
{txt}r3 {res}  -.0372022   .02049889
{reset}
{com}. 
. 
. // RESULTS OF THE PERCEIVED VIOLENCE EXPERIMENT (FIGURE 3)
. 
.         matrix results = J(3,2,0)
{txt}
{com}. 
.         local group  "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' natviol natviol_treat_`x', cluster(psu_new) 
{txt}  3{com}.                 mat results[1,1] = _b[natviol_treat_`x']
{txt}  4{com}.                 mat results[1,2] = _se[natviol_treat_`x']
{txt}  5{com}.                 mat results[2,1] = _b[treat_`x']
{txt}  6{com}.                 mat results[2,2] = _se[treat_`x']
{txt}  7{com}.                 lincom treat_`x' + natviol_treat_`x'
{txt}  8{com}.                 mat results[3,1] = r(estimate)
{txt}  9{com}.                 mat results[3,2] = r(se)
{txt} 10{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    5300
                                                       {txt}F(  3,   486) ={res}    4.23
                                                       {txt}Prob > F      = {res} 0.0058
                                                       {txt}R-squared     = {res} 0.0108
                                                       {txt}Root MSE      = {res} .25694

{txt}{ralign 89:(Std. Err. adjusted for {res:487} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0251245{col 37}{space 2} .0296855{col 48}{space 1}    0.85{col 57}{space 3}0.398{col 65}{space 4}-.0332034{col 78}{space 3} .0834523
{txt}{space 16}natviol {c |}{col 25}{res}{space 2} .0863599{col 37}{space 2} .0316784{col 48}{space 1}    2.73{col 57}{space 3}0.007{col 65}{space 4} .0241163{col 78}{space 3} .1486035
{txt}natviol_treat_militancy {c |}{col 25}{res}{space 2}-.1073786{col 37}{space 2} .0393457{col 48}{space 1}   -2.73{col 57}{space 3}0.007{col 65}{space 4}-.1846872{col 78}{space 3}-.0300699
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5973303{col 37}{space 2} .0255819{col 48}{space 1}   23.35{col 57}{space 3}0.000{col 65}{space 4} .5470654{col 78}{space 3} .6475951
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + natviol_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0822541{col 26}{space 2} .0258235{col 37}{space 1}   -3.19{col 46}{space 3}0.002{col 54}{space 4}-.1329935{col 67}{space 3}-.0315147
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         matrix list results     
{res}
{txt}results[3,2]
            c1          c2
r1 {res} -.10737858   .03934568
{txt}r2 {res}  .02512448   .02968554
{txt}r3 {res}  -.0822541   .02582346
{reset}
{com}. 
. 
. // INTERACTION BETWEEN THE RELATIVE POVERTY AND PERCEIVED VIOLENCE EXPERIMENTS (FIGURE 4)
. 
.         matrix results = J(7,2,0)
{txt}
{com}. 
.         local group  "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' n01 n10 n11 n01_treat_`x' n10_treat_`x' n11_treat_`x', cluster(psu_new) 
{txt}  3{com}.                 mat results[1,1] = _b[treat_`x']
{txt}  4{com}.                 mat results[1,2] = _se[treat_`x']
{txt}  5{com}.                 lincom treat_`x' + n01_treat_`x'
{txt}  6{com}.                 mat results[2,1] = r(estimate)
{txt}  7{com}.                 mat results[2,2] = r(se)
{txt}  8{com}.                 lincom treat_`x' + n10_treat_`x'
{txt}  9{com}.                 mat results[3,1] = r(estimate)
{txt} 10{com}.                 mat results[3,2] = r(se)
{txt} 11{com}.                 lincom treat_`x' + n11_treat_`x'
{txt} 12{com}.                 mat results[4,1] = r(estimate)
{txt} 13{com}.                 mat results[4,2] = r(se)
{txt} 14{com}.                 lincom n11_treat_`x'
{txt} 15{com}.                 mat results[5,1] = r(estimate)
{txt} 16{com}.                 mat results[5,2] = r(se)
{txt} 17{com}.                 lincom n11_treat_`x' - n10_treat_`x' 
{txt} 18{com}.                 mat results[6,1] = r(estimate)
{txt} 19{com}.                 mat results[6,2] = r(se)
{txt} 20{com}.                 lincom n11_treat_`x' - n01_treat_`x'
{txt} 21{com}.                 mat results[7,1] = r(estimate)
{txt} 22{com}.                 mat results[7,2] = r(se)        
{txt} 23{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    5300
                                                       {txt}F(  7,   486) ={res}    1.98
                                                       {txt}Prob > F      = {res} 0.0562
                                                       {txt}R-squared     = {res} 0.0126
                                                       {txt}Root MSE      = {res} .25681

{txt}{ralign 85:(Std. Err. adjusted for {res:487} clusters in psu_new)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}policy_pref_milit~y{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}treat_militancy {c |}{col 21}{res}{space 2} .0340567{col 33}{space 2} .0418165{col 44}{space 1}    0.81{col 53}{space 3}0.416{col 61}{space 4}-.0481068{col 74}{space 3} .1162202
{txt}{space 16}n01 {c |}{col 21}{res}{space 2} .0784481{col 33}{space 2} .0456006{col 44}{space 1}    1.72{col 53}{space 3}0.086{col 61}{space 4}-.0111505{col 74}{space 3} .1680468
{txt}{space 16}n10 {c |}{col 21}{res}{space 2}  .016982{col 33}{space 2} .0500968{col 44}{space 1}    0.34{col 53}{space 3}0.735{col 61}{space 4} -.081451{col 74}{space 3}  .115415
{txt}{space 16}n11 {c |}{col 21}{res}{space 2} .1087445{col 33}{space 2} .0463658{col 44}{space 1}    2.35{col 53}{space 3}0.019{col 61}{space 4} .0176423{col 74}{space 3} .1998466
{txt}n01_treat_militancy {c |}{col 21}{res}{space 2}-.0866375{col 33}{space 2} .0549559{col 44}{space 1}   -1.58{col 53}{space 3}0.116{col 61}{space 4}-.1946179{col 74}{space 3} .0213429
{txt}n10_treat_militancy {c |}{col 21}{res}{space 2}-.0196071{col 33}{space 2} .0582728{col 44}{space 1}   -0.34{col 53}{space 3}0.737{col 61}{space 4}-.1341049{col 74}{space 3} .0948907
{txt}n11_treat_militancy {c |}{col 21}{res}{space 2}-.1458224{col 33}{space 2} .0558326{col 44}{space 1}   -2.61{col 53}{space 3}0.009{col 61}{space 4}-.2555255{col 74}{space 3}-.0361193
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  .589764{col 33}{space 2} .0378309{col 44}{space 1}   15.59{col 53}{space 3}0.000{col 61}{space 4} .5154316{col 74}{space 3} .6640964
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + n01_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0525807{col 26}{space 2} .0356584{col 37}{space 1}   -1.47{col 46}{space 3}0.141{col 54}{space 4}-.1226445{col 67}{space 3}  .017483
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{p 0 7}{space 1}{text:( 1)}{space 1} {res}treat_militancy + n10_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2} .0144496{col 26}{space 2} .0405845{col 37}{space 1}    0.36{col 46}{space 3}0.722{col 54}{space 4}-.0652931{col 67}{space 3} .0941923
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{p 0 7}{space 1}{text:( 1)}{space 1} {res}treat_militancy + n11_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.1117657{col 26}{space 2} .0369954{col 37}{space 1}   -3.02{col 46}{space 3}0.003{col 54}{space 4}-.1844564{col 67}{space 3} -.039075
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{p 0 7}{space 1}{text:( 1)}{space 1} {res}n11_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.1458224{col 26}{space 2} .0558326{col 37}{space 1}   -2.61{col 46}{space 3}0.009{col 54}{space 4}-.2555255{col 67}{space 3}-.0361193
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- n10_treat_militancy + n11_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.1262153{col 26}{space 2} .0549159{col 37}{space 1}   -2.30{col 46}{space 3}0.022{col 54}{space 4}-.2341173{col 67}{space 3}-.0183133
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{p 0 7}{space 1}{text:( 1)}{space 1}{space 1}{res}- n01_treat_militancy + n11_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0591849{col 26}{space 2} .0513827{col 37}{space 1}   -1.15{col 46}{space 3}0.250{col 54}{space 4}-.1601447{col 67}{space 3} .0417748
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         matrix list results     
{res}
{txt}results[7,2]
            c1          c2
r1 {res}  .03405672   .04181652
{txt}r2 {res} -.05258075   .03565844
{txt}r3 {res}  .01444962   .04058449
{txt}r4 {res}  -.1117657   .03699541
{txt}r5 {res} -.14582242   .05583262
{txt}r6 {res} -.12621532   .05491594
{txt}r7 {res} -.05918495   .05138272
{reset}
{com}. 
. 
. // TREATMENT EFFECT OF RELATIVE POVERTY AND PERCEIVED VIOLENCE BY OBSERVED POVERTY (FIGURE 5):
. 
.         matrix results = J(3,2,0)
{txt}
{com}. 
.         local group "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' if lowexp20_urprov==1, cluster(psu_new) 
{txt}  3{com}.                 mat results[1,1] = _b[poverty_treat_`x']
{txt}  4{com}.                 mat results[1,2] = _se[poverty_treat_`x']
{txt}  5{com}.                 mat results[2,1] = _b[treat_`x']
{txt}  6{com}.                 mat results[2,2] = _se[treat_`x']
{txt}  7{com}.                 lincom treat_`x' + poverty_treat_`x'
{txt}  8{com}.                 mat results[3,1] = r(estimate)
{txt}  9{com}.                 mat results[3,2] = r(se)
{txt} 10{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    2391
                                                       {txt}F(  3,   657) ={res}    1.78
                                                       {txt}Prob > F      = {res} 0.1487
                                                       {txt}R-squared     = {res} 0.0070
                                                       {txt}Root MSE      = {res} .26941

{txt}{ralign 89:(Std. Err. adjusted for {res:658} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2}-.0320848{col 37}{space 2} .0284043{col 48}{space 1}   -1.13{col 57}{space 3}0.259{col 65}{space 4} -.087859{col 78}{space 3} .0236894
{txt}{space 16}poverty {c |}{col 25}{res}{space 2}-.0095138{col 37}{space 2} .0338016{col 48}{space 1}   -0.28{col 57}{space 3}0.778{col 65}{space 4}-.0758859{col 78}{space 3} .0568584
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0210988{col 37}{space 2} .0436796{col 48}{space 1}   -0.48{col 57}{space 3}0.629{col 65}{space 4}-.1068672{col 78}{space 3} .0646695
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .6296875{col 37}{space 2} .0209148{col 48}{space 1}   30.11{col 57}{space 3}0.000{col 65}{space 4} .5886195{col 78}{space 3} .6707555
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + poverty_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0531836{col 26}{space 2} .0331828{col 37}{space 1}   -1.60{col 46}{space 3}0.109{col 54}{space 4}-.1183408{col 67}{space 3} .0119736
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}.         
.         matrix list results
{res}
{txt}results[3,2]
            c1          c2
r1 {res} -.02109883   .04367957
{txt}r2 {res} -.03208476   .02840432
{txt}r3 {res} -.05318359   .03318282
{reset}
{com}. 
.         matrix results = J(3,2,0)
{txt}
{com}. 
.         local group "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' if lowexp20_urprov!=1, cluster(psu_new) 
{txt}  3{com}.                 mat results[1,1] = _b[poverty_treat_`x']
{txt}  4{com}.                 mat results[1,2] = _se[poverty_treat_`x']
{txt}  5{com}.                 mat results[2,1] = _b[treat_`x']
{txt}  6{com}.                 mat results[2,2] = _se[treat_`x']
{txt}  7{com}.                 lincom treat_`x' + poverty_treat_`x'
{txt}  8{com}.                 mat results[3,1] = r(estimate)
{txt}  9{com}.                 mat results[3,2] = r(se)
{txt} 10{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    8094
                                                       {txt}F(  3,   930) ={res}    1.45
                                                       {txt}Prob > F      = {res} 0.2271
                                                       {txt}R-squared     = {res} 0.0030
                                                       {txt}Root MSE      = {res} .24914

{txt}{ralign 89:(Std. Err. adjusted for {res:931} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0300644{col 37}{space 2} .0212107{col 48}{space 1}    1.42{col 57}{space 3}0.157{col 65}{space 4}-.0115621{col 78}{space 3} .0716908
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0420142{col 37}{space 2} .0249969{col 48}{space 1}    1.68{col 57}{space 3}0.093{col 65}{space 4}-.0070426{col 78}{space 3} .0910711
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0617926{col 37}{space 2} .0297177{col 48}{space 1}   -2.08{col 57}{space 3}0.038{col 65}{space 4}-.1201143{col 78}{space 3} -.003471
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .6205227{col 37}{space 2} .0182985{col 48}{space 1}   33.91{col 57}{space 3}0.000{col 65}{space 4} .5846116{col 78}{space 3} .6564339
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + poverty_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0317283{col 26}{space 2} .0208147{col 37}{space 1}   -1.52{col 46}{space 3}0.128{col 54}{space 4}-.0725774{col 67}{space 3} .0091209
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         matrix list results
{res}
{txt}results[3,2]
            c1          c2
r1 {res} -.06179264   .02971775
{txt}r2 {res}  .03006436   .02121071
{txt}r3 {res} -.03172828   .02081466
{reset}
{com}. 
.         matrix results = J(3,2,0)
{txt}
{com}. 
.         local group "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' natviol natviol_treat_`x' if lowexp20_urprov==1, cluster(psu_new) 
{txt}  3{com}.                 mat results[1,1] = _b[natviol_treat_`x']
{txt}  4{com}.                 mat results[1,2] = _se[natviol_treat_`x']
{txt}  5{com}.                 mat results[2,1] = _b[treat_`x']
{txt}  6{com}.                 mat results[2,2] = _se[treat_`x']
{txt}  7{com}.                 lincom treat_`x' + natviol_treat_`x'
{txt}  8{com}.                 mat results[3,1] = r(estimate)
{txt}  9{com}.                 mat results[3,2] = r(se)
{txt} 10{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    1165
                                                       {txt}F(  3,   329) ={res}    3.08
                                                       {txt}Prob > F      = {res} 0.0276
                                                       {txt}R-squared     = {res} 0.0280
                                                       {txt}Root MSE      = {res}  .2738

{txt}{ralign 89:(Std. Err. adjusted for {res:330} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2}  .015474{col 37}{space 2} .0446669{col 48}{space 1}    0.35{col 57}{space 3}0.729{col 65}{space 4}-.0723948{col 78}{space 3} .1033428
{txt}{space 16}natviol {c |}{col 25}{res}{space 2} .0596902{col 37}{space 2} .0467276{col 48}{space 1}    1.28{col 57}{space 3}0.202{col 65}{space 4}-.0322322{col 78}{space 3} .1516127
{txt}natviol_treat_militancy {c |}{col 25}{res}{space 2}-.1446297{col 37}{space 2} .0618347{col 48}{space 1}   -2.34{col 57}{space 3}0.020{col 65}{space 4} -.266271{col 78}{space 3}-.0229885
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5846354{col 37}{space 2} .0388682{col 48}{space 1}   15.04{col 57}{space 3}0.000{col 65}{space 4} .5081738{col 78}{space 3}  .661097
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + natviol_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.1291558{col 26}{space 2} .0427597{col 37}{space 1}   -3.02{col 46}{space 3}0.003{col 54}{space 4}-.2132727{col 67}{space 3}-.0450388
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         matrix list results
{res}
{txt}results[3,2]
            c1          c2
r1 {res} -.14462975   .06183469
{txt}r2 {res}  .01547399   .04466692
{txt}r3 {res} -.12915575   .04275973
{reset}
{com}. 
.         matrix results = J(3,2,0)
{txt}
{com}. 
.         local group "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' natviol natviol_treat_`x' if lowexp20_urprov!=1, cluster(psu_new) 
{txt}  3{com}.                 mat results[1,1] = _b[natviol_treat_`x']
{txt}  4{com}.                 mat results[1,2] = _se[natviol_treat_`x']
{txt}  5{com}.                 mat results[2,1] = _b[treat_`x']
{txt}  6{com}.                 mat results[2,2] = _se[treat_`x']
{txt}  7{com}.                 lincom treat_`x' + natviol_treat_`x'
{txt}  8{com}.                 mat results[3,1] = r(estimate)
{txt}  9{com}.                 mat results[3,2] = r(se)
{txt} 10{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    4135
                                                       {txt}F(  3,   478) ={res}    3.67
                                                       {txt}Prob > F      = {res} 0.0123
                                                       {txt}R-squared     = {res} 0.0106
                                                       {txt}Root MSE      = {res} .24994

{txt}{ralign 89:(Std. Err. adjusted for {res:479} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0285432{col 37}{space 2} .0299358{col 48}{space 1}    0.95{col 57}{space 3}0.341{col 65}{space 4}-.0302789{col 78}{space 3} .0873653
{txt}{space 16}natviol {c |}{col 25}{res}{space 2} .0942551{col 37}{space 2} .0325081{col 48}{space 1}    2.90{col 57}{space 3}0.004{col 65}{space 4} .0303786{col 78}{space 3} .1581316
{txt}natviol_treat_militancy {c |}{col 25}{res}{space 2}-.0982924{col 37}{space 2} .0398727{col 48}{space 1}   -2.47{col 57}{space 3}0.014{col 65}{space 4}-.1766398{col 78}{space 3} -.019945
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .6005773{col 37}{space 2}  .025509{col 48}{space 1}   23.54{col 57}{space 3}0.000{col 65}{space 4} .5504537{col 78}{space 3} .6507009
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{p 0 7}{space 1}{text:( 1)}{space 1} treat_militancy + natviol_treat_militancy = 0{p_end}

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}policy_pre~y{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}(1) {c |}{col 14}{res}{space 2}-.0697492{col 26}{space 2} .0263377{col 37}{space 1}   -2.65{col 46}{space 3}0.008{col 54}{space 4}-.1215013{col 67}{space 3}-.0179972
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
.         matrix list results
{res}
{txt}results[3,2]
            c1          c2
r1 {res}  -.0982924   .03987269
{txt}r2 {res}  .02854317   .02993584
{txt}r3 {res} -.06974924   .02633774
{reset}
{com}. 
. 
. // EFFECTS OF THE VIOLENCE EXPERIMENT ON POLICY RELEVANT SUB-SAMPLES
. 
.         reg policy_pref_militancy treat_militancy natviol natviol_treat_militancy if fata==1, cluster(psu_new) 

{txt}Linear regression                                      Number of obs ={res}     726
                                                       {txt}F(  3,    81) ={res}    2.38
                                                       {txt}Prob > F      = {res} 0.0760
                                                       {txt}R-squared     = {res} 0.0418
                                                       {txt}Root MSE      = {res} .23847

{txt}{ralign 89:(Std. Err. adjusted for {res:82} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .1618892{col 37}{space 2} .0628773{col 48}{space 1}    2.57{col 57}{space 3}0.012{col 65}{space 4} .0367831{col 78}{space 3} .2869954
{txt}{space 16}natviol {c |}{col 25}{res}{space 2} .1027383{col 37}{space 2} .0762082{col 48}{space 1}    1.35{col 57}{space 3}0.181{col 65}{space 4}-.0488922{col 78}{space 3} .2543688
{txt}natviol_treat_militancy {c |}{col 25}{res}{space 2}-.1543002{col 37}{space 2} .0879469{col 48}{space 1}   -1.75{col 57}{space 3}0.083{col 65}{space 4}-.3292869{col 78}{space 3} .0206864
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5538793{col 37}{space 2} .0571884{col 48}{space 1}    9.69{col 57}{space 3}0.000{col 65}{space 4} .4400923{col 78}{space 3} .6676663
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         reg policy_pref_militancy treat_militancy natviol natviol_treat_militancy if d230==4, cluster(psu_new) 

{txt}Linear regression                                      Number of obs ={res}    1690
                                                       {txt}F(  3,   190) ={res}    2.32
                                                       {txt}Prob > F      = {res} 0.0762
                                                       {txt}R-squared     = {res} 0.0181
                                                       {txt}Root MSE      = {res} .25369

{txt}{ralign 89:(Std. Err. adjusted for {res:191} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .1017973{col 37}{space 2} .0516455{col 48}{space 1}    1.97{col 57}{space 3}0.050{col 65}{space 4}-.0000749{col 78}{space 3} .2036695
{txt}{space 16}natviol {c |}{col 25}{res}{space 2} .1396553{col 37}{space 2} .0542383{col 48}{space 1}    2.57{col 57}{space 3}0.011{col 65}{space 4} .0326688{col 78}{space 3} .2466418
{txt}natviol_treat_militancy {c |}{col 25}{res}{space 2}-.1308209{col 37}{space 2} .0658056{col 48}{space 1}   -1.99{col 57}{space 3}0.048{col 65}{space 4}-.2606243{col 78}{space 3}-.0010174
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5829167{col 37}{space 2} .0434454{col 48}{space 1}   13.42{col 57}{space 3}0.000{col 65}{space 4} .4972193{col 78}{space 3}  .668614
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. ************************************************
. ****************** FOOTNOTES *******************
. ************************************************
. 
. // Footnote 16: FATA Policy Question
. 
.         tab q810a fata, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

       Do you support {c |}
    discussions about {c |}
        mainstreaming {c |}         fata
         FATA(Q810A)? {c |}         0          1 {c |}     Total
{hline 22}{c +}{hline 22}{c +}{hline 10}
         A great deal {c |}{res}       467        151 {txt}{c |}{res}       618 
                      {txt}{c |}{res}     19.68      36.74 {txt}{c |}{res}     22.20 
{txt}{hline 22}{c +}{hline 22}{c +}{hline 10}
                A lot {c |}{res}       815        100 {txt}{c |}{res}       915 
                      {txt}{c |}{res}     34.34      24.33 {txt}{c |}{res}     32.87 
{txt}{hline 22}{c +}{hline 22}{c +}{hline 10}
    A moderate amount {c |}{res}       591         53 {txt}{c |}{res}       644 
                      {txt}{c |}{res}     24.91      12.90 {txt}{c |}{res}     23.13 
{txt}{hline 22}{c +}{hline 22}{c +}{hline 10}
             A little {c |}{res}       295         58 {txt}{c |}{res}       353 
                      {txt}{c |}{res}     12.43      14.11 {txt}{c |}{res}     12.68 
{txt}{hline 22}{c +}{hline 22}{c +}{hline 10}
           Not at all {c |}{res}       205         49 {txt}{c |}{res}       254 
                      {txt}{c |}{res}      8.64      11.92 {txt}{c |}{res}      9.12 
{txt}{hline 22}{c +}{hline 22}{c +}{hline 10}
                Total {c |}{res}     2,373        411 {txt}{c |}{res}     2,784 
                      {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}
{com}.         tab fata_support fata, col
{txt}
{c TLC}{hline 19}{c TRC}
{c |} Key{col 21}{c |}
{c LT}{hline 19}{c RT}
{c |}{space 5}{it:frequency}{col 21}{c |}
{c |}{space 1}{it:column percentage}{col 21}{c |}
{c BLC}{hline 19}{c BRC}

fata_suppo {c |}         fata
        rt {c |}         0          1 {c |}     Total
{hline 11}{c +}{hline 22}{c +}{hline 10}
         0 {c |}{res}     1,091        160 {txt}{c |}{res}     1,251 
           {txt}{c |}{res}     45.98      38.93 {txt}{c |}{res}     44.94 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
         1 {c |}{res}     1,282        251 {txt}{c |}{res}     1,533 
           {txt}{c |}{res}     54.02      61.07 {txt}{c |}{res}     55.06 
{txt}{hline 11}{c +}{hline 22}{c +}{hline 10}
     Total {c |}{res}     2,373        411 {txt}{c |}{res}     2,784 
           {txt}{c |}{res}    100.00     100.00 {txt}{c |}{res}    100.00 

{txt}
{com}.         reg fata_support fata, cluster(psu_new)

{txt}Linear regression                                      Number of obs ={res}    2773
                                                       {txt}F(  1,   244) ={res}    1.60
                                                       {txt}Prob > F      = {res} 0.2066
                                                       {txt}R-squared     = {res} 0.0025
                                                       {txt}Root MSE      = {res} .49697

{txt}{ralign 78:(Std. Err. adjusted for {res:245} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}fata_support{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}fata {c |}{col 14}{res}{space 2} .0704854{col 26}{space 2} .0556662{col 37}{space 1}    1.27{col 46}{space 3}0.207{col 54}{space 4}-.0391622{col 67}{space 3} .1801331
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5402202{col 26}{space 2} .0236866{col 37}{space 1}   22.81{col 46}{space 3}0.000{col 54}{space 4} .4935639{col 67}{space 3} .5868764
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         bys fata: summ q810a

{txt}{hline}
-> fata = 0

    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 7}q810a {c |}{res}      2373    2.560051    1.186399          1          5

{txt}{hline}
-> fata = 1

    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 7}q810a {c |}{res}       411     2.40146    1.406222          1          5

{txt}
{com}.         reg q810a fata, cluster(psu_new)

{txt}Linear regression                                      Number of obs ={res}    2773
                                                       {txt}F(  1,   244) ={res}    0.97
                                                       {txt}Prob > F      = {res} 0.3264
                                                       {txt}R-squared     = {res} 0.0021
                                                       {txt}Root MSE      = {res}  1.221

{txt}{ralign 78:(Std. Err. adjusted for {res:245} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}       q810a{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}fata {c |}{col 14}{res}{space 2}-.1573886{col 26}{space 2} .1600565{col 37}{space 1}   -0.98{col 46}{space 3}0.326{col 54}{space 4}-.4726573{col 67}{space 3} .1578801
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} 2.558848{col 26}{space 2} .0598864{col 37}{space 1}   42.73{col 46}{space 3}0.000{col 54}{space 4} 2.440888{col 67}{space 3} 2.676809
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. // Footnote 22: Knowledge Diagnostic Check
. 
.         // General Knowledge Quiz as a Dummy for High / Low and as Continuous Variable
.         
.         local group  "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' knowledgehigh know_treat_`x', cluster(psu_new) 
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' knowledge knowledge_treat_`x', cluster(psu_new) 
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}    1.41
                                                       {txt}Prob > F      = {res} 0.2385
                                                       {txt}R-squared     = {res} 0.0016
                                                       {txt}Root MSE      = {res} .25494

{txt}{ralign 86:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}policy_pref_milita~y{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      t{col 54}   P>|t|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_militancy {c |}{col 22}{res}{space 2}-.0045181{col 34}{space 2} .0147698{col 45}{space 1}   -0.31{col 54}{space 3}0.760{col 62}{space 4}-.0335031{col 75}{space 3}  .024467
{txt}{space 7}knowledgehigh {c |}{col 22}{res}{space 2} .0277085{col 34}{space 2} .0169264{col 45}{space 1}    1.64{col 54}{space 3}0.102{col 62}{space 4}-.0055088{col 75}{space 3} .0609258
{txt}know_treat_militancy {c |}{col 22}{res}{space 2}-.0143668{col 34}{space 2} .0206001{col 45}{space 1}   -0.70{col 54}{space 3}0.486{col 62}{space 4}-.0547936{col 75}{space 3} .0260599
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .6254725{col 34}{space 2} .0119604{col 45}{space 1}   52.30{col 54}{space 3}0.000{col 62}{space 4} .6020008{col 75}{space 3} .6489442
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}    1.19
                                                       {txt}Prob > F      = {res} 0.3139
                                                       {txt}R-squared     = {res} 0.0014
                                                       {txt}Root MSE      = {res} .25496

{txt}{ralign 91:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 26}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 27}{c |}{col 39}    Robust
{col 1}    policy_pref_militancy{col 27}{c |}      Coef.{col 39}   Std. Err.{col 51}      t{col 59}   P>|t|{col 67}     [95% Con{col 80}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_militancy {c |}{col 27}{res}{space 2} .0307578{col 39}{space 2} .0411557{col 50}{space 1}    0.75{col 59}{space 3}0.455{col 67}{space 4}-.0500087{col 80}{space 3} .1115242
{txt}{space 16}knowledge {c |}{col 27}{res}{space 2} .0933567{col 39}{space 2} .0543588{col 50}{space 1}    1.72{col 59}{space 3}0.086{col 67}{space 4}-.0133202{col 80}{space 3} .2000337
{txt}knowledge_treat_militancy {c |}{col 27}{res}{space 2}-.0679559{col 39}{space 2} .0689289{col 50}{space 1}   -0.99{col 59}{space 3}0.324{col 67}{space 4}-.2032261{col 80}{space 3} .0673143
{txt}{space 20}_cons {c |}{col 27}{res}{space 2} .5809209{col 39}{space 2} .0324444{col 50}{space 1}   17.91{col 59}{space 3}0.000{col 67}{space 4} .5172501{col 80}{space 3} .6445917
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         matrix list results
{res}
{txt}results[3,2]
            c1          c2
r1 {res}  -.0982924   .03987269
{txt}r2 {res}  .02854317   .02993584
{txt}r3 {res} -.06974924   .02633774
{reset}
{com}. 
.         // Robustness Check with PCA Knowledge Index
. 
.         local group  "militancy"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' knowfull_high knowfullhigh_treat_`x', cluster(psu_new) 
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' knowfullpca knowfull_treat_`x', cluster(psu_new)
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}   16.11
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0185
                                                       {txt}Root MSE      = {res} .25277

{txt}{ralign 94:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 29}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 30}{c |}{col 42}    Robust
{col 1}       policy_pref_militancy{col 30}{c |}      Coef.{col 42}   Std. Err.{col 54}      t{col 62}   P>|t|{col 70}     [95% Con{col 83}f. Interval]
{hline 29}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 13}treat_militancy {c |}{col 30}{res}{space 2}-.0271187{col 42}{space 2} .0340677{col 53}{space 1}   -0.80{col 62}{space 3}0.426{col 70}{space 4}-.0939753{col 83}{space 3} .0397378
{txt}{space 15}knowfull_high {c |}{col 30}{res}{space 2} .0621142{col 42}{space 2} .0174795{col 53}{space 1}    3.55{col 62}{space 3}0.000{col 70}{space 4} .0278114{col 83}{space 3}  .096417
{txt}knowfullhigh_treat_militancy {c |}{col 30}{res}{space 2} .0090559{col 42}{space 2}  .021172{col 53}{space 1}    0.43{col 62}{space 3}0.669{col 70}{space 4}-.0324933{col 83}{space 3} .0506051
{txt}{space 23}_cons {c |}{col 30}{res}{space 2} .5449883{col 42}{space 2} .0275475{col 53}{space 1}   19.78{col 62}{space 3}0.000{col 70}{space 4} .4909274{col 83}{space 3} .5990492
{txt}{hline 29}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}   14.75
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0178
                                                       {txt}Root MSE      = {res} .25286

{txt}{ralign 90:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 25}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 26}{c |}{col 38}    Robust
{col 1}   policy_pref_militancy{col 26}{c |}      Coef.{col 38}   Std. Err.{col 50}      t{col 58}   P>|t|{col 66}     [95% Con{col 79}f. Interval]
{hline 25}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_militancy {c |}{col 26}{res}{space 2}-.0131698{col 38}{space 2} .0334849{col 49}{space 1}   -0.39{col 58}{space 3}0.694{col 66}{space 4}-.0788825{col 79}{space 3} .0525429
{txt}{space 13}knowfullpca {c |}{col 26}{res}{space 2} .0466901{col 38}{space 2}  .012065{col 49}{space 1}    3.87{col 58}{space 3}0.000{col 66}{space 4} .0230131{col 79}{space 3} .0703672
{txt}knowfull_treat_militancy {c |}{col 26}{res}{space 2}-.0002616{col 38}{space 2} .0148267{col 49}{space 1}   -0.02{col 58}{space 3}0.986{col 66}{space 4}-.0293583{col 79}{space 3} .0288352
{txt}{space 19}_cons {c |}{col 26}{res}{space 2}  .539752{col 38}{space 2} .0267553{col 49}{space 1}   20.17{col 58}{space 3}0.000{col 66}{space 4} .4872459{col 79}{space 3} .5922581
{txt}{hline 25}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. // Footnote 25: Correlation between Household Expenditures and Education
. 
.         corr d140 educ_z
{txt}(obs=15112)

             {c |}     d140   educ_z
{hline 13}{c +}{hline 18}
        d140 {c |}{res}   1.0000
      {txt}educ_z {c |}{res}   0.3142   1.0000

{txt}
{com}. 
. // Footnote 26: Effect of the Poverty Experiment on Support for Edhi
. 
.         reg policy_pref_e treat_e poverty poverty_treat_e, cluster(psu_new) 

{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F(  3,   490) ={res}    0.94
                                                       {txt}Prob > F      = {res} 0.4209
                                                       {txt}R-squared     = {res} 0.0036
                                                       {txt}Root MSE      = {res} .23633

{txt}{ralign 81:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  policy_pref_e{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_e {c |}{col 17}{res}{space 2} .0291407{col 29}{space 2} .0241551{col 40}{space 1}    1.21{col 49}{space 3}0.228{col 57}{space 4}-.0183196{col 70}{space 3}  .076601
{txt}{space 8}poverty {c |}{col 17}{res}{space 2} .0312276{col 29}{space 2} .0236439{col 40}{space 1}    1.32{col 49}{space 3}0.187{col 57}{space 4}-.0152284{col 70}{space 3} .0776836
{txt}poverty_treat_e {c |}{col 17}{res}{space 2}-.0245977{col 29}{space 2} .0337039{col 40}{space 1}   -0.73{col 49}{space 3}0.466{col 57}{space 4}-.0908197{col 70}{space 3} .0416244
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .6226903{col 29}{space 2}  .016795{col 40}{space 1}   37.08{col 49}{space 3}0.000{col 57}{space 4} .5896912{col 70}{space 3} .6556895
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. // Footnote 27: Effect of the Violence Experiment on Support for Edhi
. 
.         reg policy_pref_e treat_e natviol natviol_treat_e, cluster(psu_new) 

{txt}Linear regression                                      Number of obs ={res}    2717
                                                       {txt}F(  3,   251) ={res}    3.05
                                                       {txt}Prob > F      = {res} 0.0292
                                                       {txt}R-squared     = {res} 0.0236
                                                       {txt}Root MSE      = {res} .22868

{txt}{ralign 81:(Std. Err. adjusted for {res:252} clusters in psu_new)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  policy_pref_e{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_e {c |}{col 17}{res}{space 2} .0845803{col 29}{space 2} .0334383{col 40}{space 1}    2.53{col 49}{space 3}0.012{col 57}{space 4} .0187248{col 70}{space 3} .1504358
{txt}{space 8}natviol {c |}{col 17}{res}{space 2} .0863599{col 29}{space 2} .0317174{col 40}{space 1}    2.72{col 49}{space 3}0.007{col 57}{space 4} .0238937{col 70}{space 3} .1488261
{txt}natviol_treat_e {c |}{col 17}{res}{space 2}-.1269815{col 29}{space 2} .0460699{col 40}{space 1}   -2.76{col 49}{space 3}0.006{col 57}{space 4}-.2177143{col 70}{space 3}-.0362486
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .5973303{col 29}{space 2} .0256134{col 40}{space 1}   23.32{col 49}{space 3}0.000{col 57}{space 4} .5468857{col 70}{space 3} .6477749
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. // Footnote 29: Effect of the Poverty Experiment on Support for Edhi among Middle and Upper Class Respondents
. 
.         reg policy_pref_e treat_e poverty poverty_treat_e if lowexp20_urprov!=1, cluster(psu_new) 

{txt}Linear regression                                      Number of obs ={res}    4184
                                                       {txt}F(  3,   475) ={res}    1.59
                                                       {txt}Prob > F      = {res} 0.1920
                                                       {txt}R-squared     = {res} 0.0067
                                                       {txt}Root MSE      = {res} .23544

{txt}{ralign 81:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}  policy_pref_e{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_e {c |}{col 17}{res}{space 2} .0319773{col 29}{space 2} .0256512{col 40}{space 1}    1.25{col 49}{space 3}0.213{col 57}{space 4}-.0184265{col 70}{space 3}  .082381
{txt}{space 8}poverty {c |}{col 17}{res}{space 2} .0420142{col 29}{space 2} .0250141{col 40}{space 1}    1.68{col 49}{space 3}0.094{col 57}{space 4}-.0071377{col 70}{space 3} .0911662
{txt}poverty_treat_e {c |}{col 17}{res}{space 2}-.0227275{col 29}{space 2} .0349326{col 40}{space 1}   -0.65{col 49}{space 3}0.516{col 57}{space 4} -.091369{col 70}{space 3}  .045914
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .6205227{col 29}{space 2} .0183111{col 40}{space 1}   33.89{col 49}{space 3}0.000{col 57}{space 4} .5845419{col 70}{space 3} .6565036
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. ******************************************************
. ****************** APPENDIX TABLES *******************
. ******************************************************
. 
. use "FLMS_2015_prepped.dta", clear
{txt}
{com}. 
. *** Overview of Tables ***
. 
. * Appendix Table 1: Descriptive Statistics for Policy Support by Experimental Condition 
. * Appendix Table 2: Support for Militant Groups as Measured by the Endorsement Experiment
. * Appendix Table 3: Effects of Observed Poverty on Support for Militant Groups  
. * Appendix Table 4: Effects of Experimental Treatments on Support for Militant Groups  
. * Appendix Table 5: Effects of Experimental Treatments by Observed Poverty on Support for Militant Groups  
. * Appendix Table 6: Effects of Poverty Experiment on Support for Militant Groups when Controlling for Potential Confounding Interactions 
. 
. /// APPENDIX TABLE 1: Descriptive Statistics for Policy Support by Experimental Condition
> 
.         summ q800mil_resc if treat_group == 2 | treat_group == 3 | treat_group == 4

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
q800mil_resc {c |}{res}      8899    3.586021    1.287809          1          5
{txt}
{com}.         tab q800mil_resc if treat_group == 2 | treat_group == 3 | treat_group == 4, mi

{txt}q800mil_res {c |}
          c {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        922        9.47        9.47
{txt}          2 {c |}{res}        943        9.69       19.16
{txt}          3 {c |}{res}      1,622       16.66       35.83
{txt}          4 {c |}{res}      2,822       28.99       64.82
{txt}          5 {c |}{res}      2,590       26.61       91.43
{txt}          . {c |}{res}        834        8.57      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      9,733      100.00
{txt}
{com}.         summ q800e_resc if treat_group == 5

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}q800e_resc {c |}{res}      3108    3.768983     1.20215          1          5
{txt}
{com}.         tab q800e_resc if treat_group == 5, mi

 {txt}q800e_resc {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        232        7.06        7.06
{txt}          2 {c |}{res}        261        7.95       15.01
{txt}          3 {c |}{res}        512       15.59       30.60
{txt}          4 {c |}{res}      1,091       33.22       63.82
{txt}          5 {c |}{res}      1,012       30.82       94.64
{txt}          . {c |}{res}        176        5.36      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,284      100.00
{txt}
{com}.         summ q800a_resc if treat_group == 1

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}q800a_resc {c |}{res}      2993    3.649181    1.204054          1          5
{txt}
{com}.         tab q800a_resc if treat_group == 1, mi

 {txt}q800a_resc {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        233        7.20        7.20
{txt}          2 {c |}{res}        309        9.55       16.74
{txt}          3 {c |}{res}        553       17.08       33.83
{txt}          4 {c |}{res}      1,078       33.30       67.13
{txt}          5 {c |}{res}        820       25.33       92.46
{txt}          . {c |}{res}        244        7.54      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,237      100.00
{txt}
{com}.         
.         summ q810mil_resc if treat_group == 2 | treat_group == 3 | treat_group == 4

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
q810mil_resc {c |}{res}      8339    3.404125    1.308134          1          5
{txt}
{com}.         tab q810mil_resc if treat_group == 2 | treat_group == 3 | treat_group == 4, mi

{txt}q810mil_res {c |}
          c {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}      1,008       10.36       10.36
{txt}          2 {c |}{res}      1,033       10.61       20.97
{txt}          3 {c |}{res}      1,952       20.06       41.03
{txt}          4 {c |}{res}      2,273       23.35       64.38
{txt}          5 {c |}{res}      2,073       21.30       85.68
{txt}          . {c |}{res}      1,394       14.32      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      9,733      100.00
{txt}
{com}.         summ q810e_resc if treat_group == 5

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}q810e_resc {c |}{res}      2892    3.474758    1.265124          1          5
{txt}
{com}.         tab q810e_resc if treat_group == 5, mi

 {txt}q810e_resc {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        296        9.01        9.01
{txt}          2 {c |}{res}        356       10.84       19.85
{txt}          3 {c |}{res}        628       19.12       38.98
{txt}          4 {c |}{res}        903       27.50       66.47
{txt}          5 {c |}{res}        709       21.59       88.06
{txt}          . {c |}{res}        392       11.94      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,284      100.00
{txt}
{com}.         summ q810a_resc if treat_group == 1

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}q810a_resc {c |}{res}      2782    3.463695    1.222443          1          5
{txt}
{com}.         tab q810a_resc if treat_group == 1, mi

 {txt}q810a_resc {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        254        7.85        7.85
{txt}          2 {c |}{res}        352       10.87       18.72
{txt}          3 {c |}{res}        644       19.89       38.62
{txt}          4 {c |}{res}        914       28.24       66.85
{txt}          5 {c |}{res}        618       19.09       85.94
{txt}          . {c |}{res}        455       14.06      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,237      100.00
{txt}
{com}. 
.         summ q820mil_resc if treat_group == 2 | treat_group == 3 | treat_group == 4

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
q820mil_resc {c |}{res}      8497    3.378133    1.351224          1          5
{txt}
{com}.         tab q820mil_resc if treat_group == 2 | treat_group == 3 | treat_group == 4, mi

{txt}q820mil_res {c |}
          c {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}      1,176       12.08       12.08
{txt}          2 {c |}{res}      1,056       10.85       22.93
{txt}          3 {c |}{res}      1,817       18.67       41.60
{txt}          4 {c |}{res}      2,275       23.37       64.97
{txt}          5 {c |}{res}      2,173       22.33       87.30
{txt}          . {c |}{res}      1,236       12.70      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      9,733      100.00
{txt}
{com}.         summ q820e_resc if treat_group == 5

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}q820e_resc {c |}{res}      2927    3.496754    1.290339          1          5
{txt}
{com}.         tab q820e_resc if treat_group == 5, mi

 {txt}q820e_resc {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        310        9.44        9.44
{txt}          2 {c |}{res}        358       10.90       20.34
{txt}          3 {c |}{res}        609       18.54       38.89
{txt}          4 {c |}{res}        868       26.43       65.32
{txt}          5 {c |}{res}        782       23.81       89.13
{txt}          . {c |}{res}        357       10.87      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,284      100.00
{txt}
{com}.         summ q820a_resc if treat_a == 1

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}q820a_resc {c |}{res}      2818    3.425834    1.268246          1          5
{txt}
{com}.         tab q820a_resc if treat_a == 1, mi

 {txt}q820a_resc {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        309        9.55        9.55
{txt}          2 {c |}{res}        332       10.26       19.80
{txt}          3 {c |}{res}        689       21.29       41.09
{txt}          4 {c |}{res}        826       25.52       66.60
{txt}          5 {c |}{res}        662       20.45       87.06
{txt}          . {c |}{res}        419       12.94      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,237      100.00
{txt}
{com}. 
.         summ q830mil_resc if treat_group == 2 | treat_group == 3 | treat_group == 4

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
q830mil_resc {c |}{res}      8659    3.625361    1.321791          1          5
{txt}
{com}.         tab q830mil_resc if treat_group == 2 | treat_group == 3 | treat_group == 4, mi

{txt}q830mil_res {c |}
          c {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        888        9.12        9.12
{txt}          2 {c |}{res}        987       10.14       19.26
{txt}          3 {c |}{res}      1,504       15.45       34.72
{txt}          4 {c |}{res}      2,382       24.47       59.19
{txt}          5 {c |}{res}      2,898       29.77       88.97
{txt}          . {c |}{res}      1,074       11.03      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      9,733      100.00
{txt}
{com}.         summ q830e_resc if treat_group == 5

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}q830e_resc {c |}{res}      3026    3.784865    1.188505          1          5
{txt}
{com}.         tab q830e_resc if treat_group == 5, mi

 {txt}q830e_resc {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        181        5.51        5.51
{txt}          2 {c |}{res}        294        8.95       14.46
{txt}          3 {c |}{res}        564       17.17       31.64
{txt}          4 {c |}{res}        943       28.71       60.35
{txt}          5 {c |}{res}      1,044       31.79       92.14
{txt}          . {c |}{res}        258        7.86      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,284      100.00
{txt}
{com}.         summ q830a_resc if treat_group == 1

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}q830a_resc {c |}{res}      2899    3.659538    1.256448          1          5
{txt}
{com}.         tab q830a_resc if treat_group == 1, mi

 {txt}q830a_resc {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          1 {c |}{res}        244        7.54        7.54
{txt}          2 {c |}{res}        316        9.76       17.30
{txt}          3 {c |}{res}        537       16.59       33.89
{txt}          4 {c |}{res}        888       27.43       61.32
{txt}          5 {c |}{res}        914       28.24       89.56
{txt}          . {c |}{res}        338       10.44      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}      3,237      100.00
{txt}
{com}. 
. 
. /// APPENDIX TABLE 2: Descriptive Statistics for Policy Support by Experimental Condition
> 
. // First Panel - Endorsement effects
. 
.         local group "militancy b c d e"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x', cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' *_z *_miss, cluster(psu_new)
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  1,   952) ={res}    0.53
                                                       {txt}Prob > F      = {res} 0.4667
                                                       {txt}R-squared     = {res} 0.0003
                                                       {txt}Root MSE      = {res} .25508

{txt}{ralign 81:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 16}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 17}{c |}{col 29}    Robust
{col 1}policy_pref_m~y{col 17}{c |}      Coef.{col 29}   Std. Err.{col 41}      t{col 49}   P>|t|{col 57}     [95% Con{col 70}f. Interval]
{hline 16}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
treat_militancy {c |}{col 17}{res}{space 2}-.0104824{col 29}{space 2} .0143948{col 40}{space 1}   -0.73{col 49}{space 3}0.467{col 57}{space 4}-.0387316{col 70}{space 3} .0177667
{txt}{space 10}_cons {c |}{col 17}{res}{space 2} .6378284{col 29}{space 2} .0118716{col 40}{space 1}   53.73{col 49}{space 3}0.000{col 57}{space 4}  .614531{col 70}{space 3} .6611259
{txt}{hline 16}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 15,   952) ={res}    8.47
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0347
                                                       {txt}Root MSE      = {res} .25082

{txt}{ralign 82:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}policy_pref_mi~y{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 1}treat_militancy {c |}{col 18}{res}{space 2}-.0163044{col 30}{space 2} .0139694{col 41}{space 1}   -1.17{col 50}{space 3}0.243{col 58}{space 4}-.0437188{col 71}{space 3}   .01111
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0259416{col 30}{space 2} .0136397{col 41}{space 1}    1.90{col 50}{space 3}0.057{col 58}{space 4}-.0008257{col 71}{space 3} .0527089
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0040878{col 30}{space 2} .0094224{col 41}{space 1}   -0.43{col 50}{space 3}0.665{col 58}{space 4}-.0225788{col 71}{space 3} .0144032
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0287135{col 30}{space 2} .0215715{col 41}{space 1}    1.33{col 50}{space 3}0.183{col 58}{space 4}-.0136196{col 71}{space 3} .0710467
{txt}{space 10}read_z {c |}{col 18}{res}{space 2} -.020035{col 30}{space 2} .0121841{col 41}{space 1}   -1.64{col 50}{space 3}0.100{col 58}{space 4}-.0439458{col 71}{space 3} .0038758
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0637958{col 30}{space 2} .0140269{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .0362687{col 71}{space 3} .0913229
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0557406{col 30}{space 2} .0198034{col 41}{space 1}    2.81{col 50}{space 3}0.005{col 58}{space 4} .0168772{col 71}{space 3}  .094604
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2}    .2333{col 30}{space 2} .0416409{col 41}{space 1}    5.60{col 50}{space 3}0.000{col 58}{space 4} .1515815{col 71}{space 3} .3150186
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0477196{col 30}{space 2} .0366885{col 41}{space 1}   -1.30{col 50}{space 3}0.194{col 58}{space 4}-.1197193{col 71}{space 3} .0242802
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}-.0393189{col 30}{space 2} .0495744{col 41}{space 1}   -0.79{col 50}{space 3}0.428{col 58}{space 4}-.1366065{col 71}{space 3} .0579687
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .1805889{col 30}{space 2} .0509258{col 41}{space 1}    3.55{col 50}{space 3}0.000{col 58}{space 4}  .080649{col 71}{space 3} .2805288
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0807394{col 30}{space 2} .0396784{col 41}{space 1}   -2.03{col 50}{space 3}0.042{col 58}{space 4}-.1586066{col 71}{space 3}-.0028722
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0856561{col 30}{space 2} .0172102{col 41}{space 1}    4.98{col 50}{space 3}0.000{col 58}{space 4} .0518818{col 71}{space 3} .1194304
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2}  .127452{col 30}{space 2} .0577848{col 41}{space 1}    2.21{col 50}{space 3}0.028{col 58}{space 4} .0140518{col 71}{space 3} .2408523
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0760118{col 30}{space 2} .0182781{col 41}{space 1}    4.16{col 50}{space 3}0.000{col 58}{space 4} .0401418{col 71}{space 3} .1118818
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5434191{col 30}{space 2} .0228578{col 41}{space 1}   23.77{col 50}{space 3}0.000{col 58}{space 4} .4985616{col 71}{space 3} .5882766
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F(  1,   474) ={res}    0.02
                                                       {txt}Prob > F      = {res} 0.8972
                                                       {txt}R-squared     = {res} 0.0000
                                                       {txt}Root MSE      = {res} .24495

{txt}{ralign 78:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~b{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_b {c |}{col 14}{res}{space 2}-.0023256{col 26}{space 2} .0179891{col 37}{space 1}   -0.13{col 46}{space 3}0.897{col 54}{space 4}-.0376738{col 67}{space 3} .0330225
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6378284{col 26}{space 2} .0118784{col 37}{space 1}   53.70{col 46}{space 3}0.000{col 54}{space 4} .6144876{col 67}{space 3} .6611693
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F( 15,   474) ={res}    4.87
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0312
                                                       {txt}Root MSE      = {res} .24142

{txt}{ralign 82:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_b{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_b {c |}{col 18}{res}{space 2} -.007325{col 30}{space 2} .0173834{col 41}{space 1}   -0.42{col 50}{space 3}0.674{col 58}{space 4} -.041483{col 71}{space 3}  .026833
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0154626{col 30}{space 2} .0177677{col 41}{space 1}    0.87{col 50}{space 3}0.385{col 58}{space 4}-.0194506{col 71}{space 3} .0503759
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2} .0110601{col 30}{space 2} .0127537{col 41}{space 1}    0.87{col 50}{space 3}0.386{col 58}{space 4}-.0140007{col 71}{space 3} .0361208
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0195475{col 30}{space 2}   .02943{col 41}{space 1}    0.66{col 50}{space 3}0.507{col 58}{space 4} -.038282{col 71}{space 3}  .077377
{txt}{space 10}read_z {c |}{col 18}{res}{space 2}-.0399868{col 30}{space 2} .0157623{col 41}{space 1}   -2.54{col 50}{space 3}0.012{col 58}{space 4}-.0709595{col 71}{space 3}-.0090141
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0716251{col 30}{space 2} .0168636{col 41}{space 1}    4.25{col 50}{space 3}0.000{col 58}{space 4} .0384884{col 71}{space 3} .1047619
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0691471{col 30}{space 2} .0253736{col 41}{space 1}    2.73{col 50}{space 3}0.007{col 58}{space 4} .0192884{col 71}{space 3} .1190058
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .1428018{col 30}{space 2} .0571119{col 41}{space 1}    2.50{col 50}{space 3}0.013{col 58}{space 4}  .030578{col 71}{space 3} .2550256
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2} .0061086{col 30}{space 2} .0488362{col 41}{space 1}    0.13{col 50}{space 3}0.901{col 58}{space 4}-.0898535{col 71}{space 3} .1020707
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}-.0217957{col 30}{space 2} .0563636{col 41}{space 1}   -0.39{col 50}{space 3}0.699{col 58}{space 4}-.1325492{col 71}{space 3} .0889577
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .2056402{col 30}{space 2}  .051485{col 41}{space 1}    3.99{col 50}{space 3}0.000{col 58}{space 4} .1044731{col 71}{space 3} .3068073
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0952052{col 30}{space 2} .0595168{col 41}{space 1}   -1.60{col 50}{space 3}0.110{col 58}{space 4}-.2121547{col 71}{space 3} .0217443
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0917191{col 30}{space 2} .0206038{col 41}{space 1}    4.45{col 50}{space 3}0.000{col 58}{space 4} .0512329{col 71}{space 3} .1322053
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2}  .045334{col 30}{space 2} .0627101{col 41}{space 1}    0.72{col 50}{space 3}0.470{col 58}{space 4}-.0778901{col 71}{space 3} .1685581
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0582696{col 30}{space 2} .0227681{col 41}{space 1}    2.56{col 50}{space 3}0.011{col 58}{space 4} .0135308{col 71}{space 3} .1030084
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5361563{col 30}{space 2} .0288994{col 41}{space 1}   18.55{col 50}{space 3}0.000{col 58}{space 4} .4793696{col 71}{space 3}  .592943
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F(  1,   475) ={res}    0.27
                                                       {txt}Prob > F      = {res} 0.6068
                                                       {txt}R-squared     = {res} 0.0004
                                                       {txt}Root MSE      = {res} .24526

{txt}{ralign 78:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~c{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_c {c |}{col 14}{res}{space 2}-.0094385{col 26}{space 2} .0183262{col 37}{space 1}   -0.52{col 46}{space 3}0.607{col 54}{space 4} -.045449{col 67}{space 3} .0265721
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6378284{col 26}{space 2} .0118784{col 37}{space 1}   53.70{col 46}{space 3}0.000{col 54}{space 4} .6144878{col 67}{space 3} .6611691
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F( 15,   475) ={res}    3.89
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0310
                                                       {txt}Root MSE      = {res} .24179

{txt}{ralign 82:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_c{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_c {c |}{col 18}{res}{space 2}-.0164499{col 30}{space 2} .0178512{col 41}{space 1}   -0.92{col 50}{space 3}0.357{col 58}{space 4}-.0515269{col 71}{space 3} .0186272
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0314286{col 30}{space 2} .0184683{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0048611{col 71}{space 3} .0677183
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0246579{col 30}{space 2} .0128216{col 41}{space 1}   -1.92{col 50}{space 3}0.055{col 58}{space 4} -.049852{col 71}{space 3} .0005362
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0410968{col 30}{space 2} .0298956{col 41}{space 1}    1.37{col 50}{space 3}0.170{col 58}{space 4}-.0176471{col 71}{space 3} .0998407
{txt}{space 10}read_z {c |}{col 18}{res}{space 2} .0061624{col 30}{space 2} .0162885{col 41}{space 1}    0.38{col 50}{space 3}0.705{col 58}{space 4} -.025844{col 71}{space 3} .0381688
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0558232{col 30}{space 2} .0189397{col 41}{space 1}    2.95{col 50}{space 3}0.003{col 58}{space 4} .0186073{col 71}{space 3} .0930391
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0402984{col 30}{space 2}  .026858{col 41}{space 1}    1.50{col 50}{space 3}0.134{col 58}{space 4}-.0124768{col 71}{space 3} .0930736
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .0865813{col 30}{space 2} .0598005{col 41}{space 1}    1.45{col 50}{space 3}0.148{col 58}{space 4}-.0309251{col 71}{space 3} .2040876
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2} .0141556{col 30}{space 2} .0528885{col 41}{space 1}    0.27{col 50}{space 3}0.789{col 58}{space 4}-.0897687{col 71}{space 3} .1180799
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}  .001392{col 30}{space 2} .0890583{col 41}{space 1}    0.02{col 50}{space 3}0.988{col 58}{space 4} -.173605{col 71}{space 3} .1763889
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .2247949{col 30}{space 2} .0756372{col 41}{space 1}    2.97{col 50}{space 3}0.003{col 58}{space 4}   .07617{col 71}{space 3} .3734198
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0019957{col 30}{space 2} .0459805{col 41}{space 1}   -0.04{col 50}{space 3}0.965{col 58}{space 4} -.092346{col 71}{space 3} .0883546
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0924649{col 30}{space 2} .0234651{col 41}{space 1}    3.94{col 50}{space 3}0.000{col 58}{space 4} .0463566{col 71}{space 3} .1385731
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2} .1411572{col 30}{space 2} .1011913{col 41}{space 1}    1.39{col 50}{space 3}0.164{col 58}{space 4}-.0576807{col 71}{space 3} .3399951
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0467799{col 30}{space 2} .0239947{col 41}{space 1}    1.95{col 50}{space 3}0.052{col 58}{space 4} -.000369{col 71}{space 3} .0939288
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5367998{col 30}{space 2} .0304288{col 41}{space 1}   17.64{col 50}{space 3}0.000{col 58}{space 4} .4770081{col 71}{space 3} .5965915
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F(  1,   483) ={res}    1.10
                                                       {txt}Prob > F      = {res} 0.2945
                                                       {txt}R-squared     = {res} 0.0015
                                                       {txt}Root MSE      = {res} .25366

{txt}{ralign 78:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~d{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_d {c |}{col 14}{res}{space 2}-.0199478{col 26}{space 2} .0190098{col 37}{space 1}   -1.05{col 46}{space 3}0.295{col 54}{space 4}-.0572998{col 67}{space 3} .0174043
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6378284{col 26}{space 2} .0118782{col 37}{space 1}   53.70{col 46}{space 3}0.000{col 54}{space 4} .6144891{col 67}{space 3} .6611678
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F( 15,   483) ={res}    5.06
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0437
                                                       {txt}Root MSE      = {res} .24859

{txt}{ralign 82:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_d{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_d {c |}{col 18}{res}{space 2}-.0235691{col 30}{space 2} .0183321{col 41}{space 1}   -1.29{col 50}{space 3}0.199{col 58}{space 4}-.0595897{col 71}{space 3} .0124515
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0232445{col 30}{space 2} .0192482{col 41}{space 1}    1.21{col 50}{space 3}0.228{col 58}{space 4} -.014576{col 71}{space 3} .0610651
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0036477{col 30}{space 2} .0144893{col 41}{space 1}   -0.25{col 50}{space 3}0.801{col 58}{space 4}-.0321175{col 71}{space 3} .0248222
{txt}{space 11}age_z {c |}{col 18}{res}{space 2}  .029583{col 30}{space 2} .0324954{col 41}{space 1}    0.91{col 50}{space 3}0.363{col 58}{space 4}-.0342668{col 71}{space 3} .0934328
{txt}{space 10}read_z {c |}{col 18}{res}{space 2}-.0110184{col 30}{space 2} .0166424{col 41}{space 1}   -0.66{col 50}{space 3}0.508{col 58}{space 4}-.0437188{col 71}{space 3}  .021682
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0785579{col 30}{space 2} .0201444{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .0389764{col 71}{space 3} .1181394
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0524152{col 30}{space 2} .0262407{col 41}{space 1}    2.00{col 50}{space 3}0.046{col 58}{space 4} .0008552{col 71}{space 3} .1039753
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .2305008{col 30}{space 2} .0587461{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .1150713{col 71}{space 3} .3459303
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0572227{col 30}{space 2}  .051063{col 41}{space 1}   -1.12{col 50}{space 3}0.263{col 58}{space 4}-.1575557{col 71}{space 3} .0431102
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}-.0705276{col 30}{space 2} .0838025{col 41}{space 1}   -0.84{col 50}{space 3}0.400{col 58}{space 4}  -.23519{col 71}{space 3} .0941349
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .1062536{col 30}{space 2} .0868846{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4}-.0644648{col 71}{space 3}  .276972
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2} -.085164{col 30}{space 2}  .056709{col 41}{space 1}   -1.50{col 50}{space 3}0.134{col 58}{space 4}-.1965908{col 71}{space 3} .0262628
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .1077432{col 30}{space 2}  .025693{col 41}{space 1}    4.19{col 50}{space 3}0.000{col 58}{space 4} .0572593{col 71}{space 3} .1582272
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2}  .153311{col 30}{space 2} .0827777{col 41}{space 1}    1.85{col 50}{space 3}0.065{col 58}{space 4}-.0093378{col 71}{space 3} .3159598
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0752635{col 30}{space 2} .0255572{col 41}{space 1}    2.94{col 50}{space 3}0.003{col 58}{space 4} .0250464{col 71}{space 3} .1254806
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5338724{col 30}{space 2} .0302921{col 41}{space 1}   17.62{col 50}{space 3}0.000{col 58}{space 4} .4743519{col 71}{space 3}  .593393
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F(  1,   490) ={res}    1.05
                                                       {txt}Prob > F      = {res} 0.3060
                                                       {txt}R-squared     = {res} 0.0013
                                                       {txt}Root MSE      = {res} .23655

{txt}{ralign 78:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_e {c |}{col 14}{res}{space 2} .0173079{col 26}{space 2} .0168909{col 37}{space 1}    1.02{col 46}{space 3}0.306{col 54}{space 4}-.0158796{col 67}{space 3} .0504954
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6378284{col 26}{space 2}  .011878{col 37}{space 1}   53.70{col 46}{space 3}0.000{col 54}{space 4} .6144904{col 67}{space 3} .6611665
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F( 15,   490) ={res}    4.82
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0451
                                                       {txt}Root MSE      = {res} .23161

{txt}{ralign 82:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_e {c |}{col 18}{res}{space 2} .0104044{col 30}{space 2} .0163573{col 41}{space 1}    0.64{col 50}{space 3}0.525{col 58}{space 4}-.0217347{col 71}{space 3} .0425435
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2}  .039497{col 30}{space 2} .0174576{col 41}{space 1}    2.26{col 50}{space 3}0.024{col 58}{space 4}  .005196{col 71}{space 3}  .073798
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0072356{col 30}{space 2} .0124106{col 41}{space 1}   -0.58{col 50}{space 3}0.560{col 58}{space 4}-.0316203{col 71}{space 3}  .017149
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0031414{col 30}{space 2} .0303558{col 41}{space 1}    0.10{col 50}{space 3}0.918{col 58}{space 4}-.0565022{col 71}{space 3}  .062785
{txt}{space 10}read_z {c |}{col 18}{res}{space 2}-.0021665{col 30}{space 2} .0154869{col 41}{space 1}   -0.14{col 50}{space 3}0.889{col 58}{space 4}-.0325955{col 71}{space 3} .0282625
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0760825{col 30}{space 2} .0173305{col 41}{space 1}    4.39{col 50}{space 3}0.000{col 58}{space 4} .0420312{col 71}{space 3} .1101338
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0326732{col 30}{space 2} .0250976{col 41}{space 1}    1.30{col 50}{space 3}0.194{col 58}{space 4}-.0166391{col 71}{space 3} .0819854
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .0919913{col 30}{space 2} .0522186{col 41}{space 1}    1.76{col 50}{space 3}0.079{col 58}{space 4}-.0106086{col 71}{space 3} .1945912
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0168227{col 30}{space 2} .0472457{col 41}{space 1}   -0.36{col 50}{space 3}0.722{col 58}{space 4}-.1096519{col 71}{space 3} .0760066
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2} .0637666{col 30}{space 2} .0513442{col 41}{space 1}    1.24{col 50}{space 3}0.215{col 58}{space 4}-.0371154{col 71}{space 3} .1646486
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .0043654{col 30}{space 2} .0697614{col 41}{space 1}    0.06{col 50}{space 3}0.950{col 58}{space 4}-.1327029{col 71}{space 3} .1414338
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0130712{col 30}{space 2} .0489284{col 41}{space 1}   -0.27{col 50}{space 3}0.789{col 58}{space 4}-.1092066{col 71}{space 3} .0830642
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0834253{col 30}{space 2} .0247338{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4} .0348278{col 71}{space 3} .1320227
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2}-.1990325{col 30}{space 2} .0601961{col 41}{space 1}   -3.31{col 50}{space 3}0.001{col 58}{space 4}-.3173068{col 71}{space 3}-.0807582
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0503383{col 30}{space 2} .0231569{col 41}{space 1}    2.17{col 50}{space 3}0.030{col 58}{space 4} .0048392{col 71}{space 3} .0958374
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5418518{col 30}{space 2} .0273609{col 41}{space 1}   19.80{col 50}{space 3}0.000{col 58}{space 4} .4880927{col 71}{space 3} .5956109
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. // Second Panel - Endorsement condition interacted with knowledge index
.         
.         local group "militancy b c d e"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' knowledge knowledge_treat_`x', cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' knowledge knowledge_treat_`x' *_z *_miss, cluster(psu_new)        
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}    1.19
                                                       {txt}Prob > F      = {res} 0.3139
                                                       {txt}R-squared     = {res} 0.0014
                                                       {txt}Root MSE      = {res} .25496

{txt}{ralign 91:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 26}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 27}{c |}{col 39}    Robust
{col 1}    policy_pref_militancy{col 27}{c |}      Coef.{col 39}   Std. Err.{col 51}      t{col 59}   P>|t|{col 67}     [95% Con{col 80}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_militancy {c |}{col 27}{res}{space 2} .0307578{col 39}{space 2} .0411557{col 50}{space 1}    0.75{col 59}{space 3}0.455{col 67}{space 4}-.0500087{col 80}{space 3} .1115242
{txt}{space 16}knowledge {c |}{col 27}{res}{space 2} .0933567{col 39}{space 2} .0543588{col 50}{space 1}    1.72{col 59}{space 3}0.086{col 67}{space 4}-.0133202{col 80}{space 3} .2000337
{txt}knowledge_treat_militancy {c |}{col 27}{res}{space 2}-.0679559{col 39}{space 2} .0689289{col 50}{space 1}   -0.99{col 59}{space 3}0.324{col 67}{space 4}-.2032261{col 80}{space 3} .0673143
{txt}{space 20}_cons {c |}{col 27}{res}{space 2} .5809209{col 39}{space 2} .0324444{col 50}{space 1}   17.91{col 59}{space 3}0.000{col 67}{space 4} .5172501{col 80}{space 3} .6445917
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 17,   952) ={res}    7.59
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0354
                                                       {txt}Root MSE      = {res} .25076

{txt}{ralign 91:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 26}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 27}{c |}{col 39}    Robust
{col 1}    policy_pref_militancy{col 27}{c |}      Coef.{col 39}   Std. Err.{col 51}      t{col 59}   P>|t|{col 67}     [95% Con{col 80}f. Interval]
{hline 26}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_militancy {c |}{col 27}{res}{space 2} .0273357{col 39}{space 2} .0398732{col 50}{space 1}    0.69{col 59}{space 3}0.493{col 67}{space 4}-.0509138{col 80}{space 3} .1055853
{txt}{space 16}knowledge {c |}{col 27}{res}{space 2} .0262132{col 39}{space 2} .0531306{col 50}{space 1}    0.49{col 59}{space 3}0.622{col 67}{space 4}-.0780535{col 80}{space 3} .1304798
{txt}knowledge_treat_militancy {c |}{col 27}{res}{space 2} -.071168{col 39}{space 2} .0667832{col 50}{space 1}   -1.07{col 59}{space 3}0.287{col 67}{space 4}-.2022273{col 80}{space 3} .0598913
{txt}{space 17}gender_z {c |}{col 27}{res}{space 2} .0274136{col 39}{space 2} .0138769{col 50}{space 1}    1.98{col 59}{space 3}0.049{col 67}{space 4} .0001808{col 80}{space 3} .0546464
{txt}{space 18}headh_z {c |}{col 27}{res}{space 2} -.004392{col 39}{space 2} .0094093{col 50}{space 1}   -0.47{col 59}{space 3}0.641{col 67}{space 4}-.0228574{col 80}{space 3} .0140734
{txt}{space 20}age_z {c |}{col 27}{res}{space 2} .0296787{col 39}{space 2} .0215431{col 50}{space 1}    1.38{col 59}{space 3}0.169{col 67}{space 4}-.0125988{col 80}{space 3} .0719562
{txt}{space 19}read_z {c |}{col 27}{res}{space 2}-.0196075{col 39}{space 2} .0121738{col 50}{space 1}   -1.61{col 59}{space 3}0.108{col 67}{space 4} -.043498{col 80}{space 3} .0042831
{txt}{space 19}math_z {c |}{col 27}{res}{space 2} .0645619{col 39}{space 2} .0137707{col 50}{space 1}    4.69{col 59}{space 3}0.000{col 67}{space 4} .0375376{col 80}{space 3} .0915863
{txt}{space 19}educ_z {c |}{col 27}{res}{space 2} .0568444{col 39}{space 2} .0200503{col 50}{space 1}    2.84{col 59}{space 3}0.005{col 67}{space 4} .0174965{col 80}{space 3} .0961922
{txt}{space 12}houseexpend_z {c |}{col 27}{res}{space 2} .2366658{col 39}{space 2} .0412673{col 50}{space 1}    5.73{col 59}{space 3}0.000{col 67}{space 4} .1556804{col 80}{space 3} .3176511
{txt}{space 13}assetindex_z {c |}{col 27}{res}{space 2}-.0441887{col 39}{space 2} .0376807{col 50}{space 1}   -1.17{col 59}{space 3}0.241{col 67}{space 4}-.1181356{col 80}{space 3} .0297582
{txt}{space 15}headh_miss {c |}{col 27}{res}{space 2}-.0406289{col 39}{space 2} .0493754{col 50}{space 1}   -0.82{col 59}{space 3}0.411{col 67}{space 4}-.1375261{col 80}{space 3} .0562683
{txt}{space 17}age_miss {c |}{col 27}{res}{space 2} .1781816{col 39}{space 2} .0507782{col 50}{space 1}    3.51{col 59}{space 3}0.000{col 67}{space 4} .0785315{col 80}{space 3} .2778316
{txt}{space 16}read_miss {c |}{col 27}{res}{space 2}-.0821283{col 39}{space 2} .0402858{col 50}{space 1}   -2.04{col 59}{space 3}0.042{col 67}{space 4}-.1611876{col 80}{space 3} -.003069
{txt}{space 16}math_miss {c |}{col 27}{res}{space 2} .0859084{col 39}{space 2} .0173101{col 50}{space 1}    4.96{col 59}{space 3}0.000{col 67}{space 4} .0519381{col 80}{space 3} .1198788
{txt}{space 16}educ_miss {c |}{col 27}{res}{space 2} .1253985{col 39}{space 2} .0578749{col 50}{space 1}    2.17{col 59}{space 3}0.031{col 67}{space 4} .0118213{col 80}{space 3} .2389757
{txt}{space 9}houseexpend_miss {c |}{col 27}{res}{space 2} .0762865{col 39}{space 2} .0182737{col 50}{space 1}    4.17{col 59}{space 3}0.000{col 67}{space 4} .0404252{col 80}{space 3} .1121479
{txt}{space 20}_cons {c |}{col 27}{res}{space 2} .5230947{col 39}{space 2} .0351311{col 50}{space 1}   14.89{col 59}{space 3}0.000{col 67}{space 4} .4541514{col 80}{space 3} .5920379
{txt}{hline 26}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F(  3,   474) ={res}    0.99
                                                       {txt}Prob > F      = {res} 0.3980
                                                       {txt}R-squared     = {res} 0.0020
                                                       {txt}Root MSE      = {res} .24475

{txt}{ralign 83:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}    policy_pref_b{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_b {c |}{col 19}{res}{space 2} .0521822{col 31}{space 2} .0577741{col 42}{space 1}    0.90{col 51}{space 3}0.367{col 59}{space 4}-.0613429{col 72}{space 3} .1657073
{txt}{space 8}knowledge {c |}{col 19}{res}{space 2} .0933567{col 31}{space 2} .0543952{col 42}{space 1}    1.72{col 51}{space 3}0.087{col 59}{space 4}-.0135289{col 72}{space 3} .2002423
{txt}knowledge_treat_b {c |}{col 19}{res}{space 2}-.0894873{col 31}{space 2} .0971082{col 42}{space 1}   -0.92{col 51}{space 3}0.357{col 59}{space 4} -.280303{col 72}{space 3} .1013284
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5809209{col 31}{space 2} .0324661{col 42}{space 1}   17.89{col 51}{space 3}0.000{col 59}{space 4} .5171255{col 72}{space 3} .6447163
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F( 17,   474) ={res}    4.60
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0323
                                                       {txt}Root MSE      = {res} .24133

{txt}{ralign 83:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}    policy_pref_b{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_b {c |}{col 19}{res}{space 2} .0544048{col 31}{space 2} .0566965{col 42}{space 1}    0.96{col 51}{space 3}0.338{col 59}{space 4}-.0570026{col 72}{space 3} .1658123
{txt}{space 8}knowledge {c |}{col 19}{res}{space 2} .0347432{col 31}{space 2}   .05357{col 42}{space 1}    0.65{col 51}{space 3}0.517{col 59}{space 4}-.0705209{col 72}{space 3} .1400073
{txt}knowledge_treat_b {c |}{col 19}{res}{space 2}-.1002701{col 31}{space 2} .0948412{col 42}{space 1}   -1.06{col 51}{space 3}0.291{col 59}{space 4}-.2866313{col 72}{space 3} .0860912
{txt}{space 9}gender_z {c |}{col 19}{res}{space 2} .0165942{col 31}{space 2} .0178628{col 42}{space 1}    0.93{col 51}{space 3}0.353{col 59}{space 4}-.0185059{col 72}{space 3} .0516942
{txt}{space 10}headh_z {c |}{col 19}{res}{space 2} .0102669{col 31}{space 2} .0125938{col 42}{space 1}    0.82{col 51}{space 3}0.415{col 59}{space 4}-.0144797{col 72}{space 3} .0350135
{txt}{space 12}age_z {c |}{col 19}{res}{space 2} .0214058{col 31}{space 2}  .029335{col 42}{space 1}    0.73{col 51}{space 3}0.466{col 59}{space 4} -.036237{col 72}{space 3} .0790486
{txt}{space 11}read_z {c |}{col 19}{res}{space 2}    -.039{col 31}{space 2} .0157011{col 42}{space 1}   -2.48{col 51}{space 3}0.013{col 59}{space 4}-.0698523{col 72}{space 3}-.0081477
{txt}{space 11}math_z {c |}{col 19}{res}{space 2} .0719355{col 31}{space 2} .0165099{col 42}{space 1}    4.36{col 51}{space 3}0.000{col 59}{space 4} .0394938{col 72}{space 3} .1043772
{txt}{space 11}educ_z {c |}{col 19}{res}{space 2} .0693659{col 31}{space 2} .0257347{col 42}{space 1}    2.70{col 51}{space 3}0.007{col 59}{space 4} .0187977{col 72}{space 3} .1199342
{txt}{space 4}houseexpend_z {c |}{col 19}{res}{space 2} .1427767{col 31}{space 2} .0568671{col 42}{space 1}    2.51{col 51}{space 3}0.012{col 59}{space 4}  .031034{col 72}{space 3} .2545195
{txt}{space 5}assetindex_z {c |}{col 19}{res}{space 2} .0090125{col 31}{space 2} .0502042{col 42}{space 1}    0.18{col 51}{space 3}0.858{col 59}{space 4}-.0896378{col 72}{space 3} .1076629
{txt}{space 7}headh_miss {c |}{col 19}{res}{space 2}-.0238084{col 31}{space 2} .0556062{col 42}{space 1}   -0.43{col 51}{space 3}0.669{col 59}{space 4}-.1330736{col 72}{space 3} .0854568
{txt}{space 9}age_miss {c |}{col 19}{res}{space 2} .2028584{col 31}{space 2} .0493787{col 42}{space 1}    4.11{col 51}{space 3}0.000{col 59}{space 4} .1058301{col 72}{space 3} .2998867
{txt}{space 8}read_miss {c |}{col 19}{res}{space 2}-.0964649{col 31}{space 2} .0610607{col 42}{space 1}   -1.58{col 51}{space 3}0.115{col 59}{space 4} -.216448{col 72}{space 3} .0235182
{txt}{space 8}math_miss {c |}{col 19}{res}{space 2}  .091985{col 31}{space 2} .0207184{col 42}{space 1}    4.44{col 51}{space 3}0.000{col 59}{space 4} .0512737{col 72}{space 3} .1326962
{txt}{space 8}educ_miss {c |}{col 19}{res}{space 2} .0474527{col 31}{space 2} .0635721{col 42}{space 1}    0.75{col 51}{space 3}0.456{col 59}{space 4}-.0774652{col 72}{space 3} .1723707
{txt}{space 1}houseexpend_miss {c |}{col 19}{res}{space 2} .0597379{col 31}{space 2} .0228857{col 42}{space 1}    2.61{col 51}{space 3}0.009{col 59}{space 4}  .014768{col 72}{space 3} .1047078
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5119083{col 31}{space 2} .0382591{col 42}{space 1}   13.38{col 51}{space 3}0.000{col 59}{space 4} .4367299{col 72}{space 3} .5870868
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F(  3,   475) ={res}    1.27
                                                       {txt}Prob > F      = {res} 0.2854
                                                       {txt}R-squared     = {res} 0.0029
                                                       {txt}Root MSE      = {res} .24499

{txt}{ralign 83:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}    policy_pref_c{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_c {c |}{col 19}{res}{space 2} .0161408{col 31}{space 2} .0494406{col 42}{space 1}    0.33{col 51}{space 3}0.744{col 59}{space 4}-.0810086{col 72}{space 3} .1132901
{txt}{space 8}knowledge {c |}{col 19}{res}{space 2} .0933567{col 31}{space 2} .0543952{col 42}{space 1}    1.72{col 51}{space 3}0.087{col 59}{space 4}-.0135283{col 72}{space 3} .2002418
{txt}knowledge_treat_c {c |}{col 19}{res}{space 2}-.0423487{col 31}{space 2} .0833659{col 42}{space 1}   -0.51{col 51}{space 3}0.612{col 59}{space 4}-.2061603{col 72}{space 3} .1214629
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5809209{col 31}{space 2} .0324661{col 42}{space 1}   17.89{col 51}{space 3}0.000{col 59}{space 4} .5171258{col 72}{space 3} .6447159
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F( 17,   475) ={res}    3.48
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0313
                                                       {txt}Root MSE      = {res}  .2418

{txt}{ralign 83:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}    policy_pref_c{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_c {c |}{col 19}{res}{space 2} .0105536{col 31}{space 2} .0482595{col 42}{space 1}    0.22{col 51}{space 3}0.827{col 59}{space 4} -.084275{col 72}{space 3} .1053822
{txt}{space 8}knowledge {c |}{col 19}{res}{space 2} .0376307{col 31}{space 2} .0530887{col 42}{space 1}    0.71{col 51}{space 3}0.479{col 59}{space 4} -.066687{col 72}{space 3} .1419484
{txt}knowledge_treat_c {c |}{col 19}{res}{space 2}-.0439662{col 31}{space 2} .0815015{col 42}{space 1}   -0.54{col 51}{space 3}0.590{col 59}{space 4}-.2041142{col 72}{space 3} .1161819
{txt}{space 9}gender_z {c |}{col 19}{res}{space 2} .0297633{col 31}{space 2} .0185421{col 42}{space 1}    1.61{col 51}{space 3}0.109{col 59}{space 4}-.0066714{col 72}{space 3}  .066198
{txt}{space 10}headh_z {c |}{col 19}{res}{space 2}-.0244275{col 31}{space 2} .0128202{col 42}{space 1}   -1.91{col 51}{space 3}0.057{col 59}{space 4}-.0496188{col 72}{space 3} .0007638
{txt}{space 12}age_z {c |}{col 19}{res}{space 2}  .042172{col 31}{space 2} .0298969{col 42}{space 1}    1.41{col 51}{space 3}0.159{col 59}{space 4}-.0165745{col 72}{space 3} .1009185
{txt}{space 11}read_z {c |}{col 19}{res}{space 2} .0064661{col 31}{space 2}   .01631{col 42}{space 1}    0.40{col 51}{space 3}0.692{col 59}{space 4}-.0255825{col 72}{space 3} .0385147
{txt}{space 11}math_z {c |}{col 19}{res}{space 2}  .055077{col 31}{space 2} .0187849{col 42}{space 1}    2.93{col 51}{space 3}0.004{col 59}{space 4} .0181653{col 72}{space 3} .0919888
{txt}{space 11}educ_z {c |}{col 19}{res}{space 2} .0396115{col 31}{space 2} .0272807{col 42}{space 1}    1.45{col 51}{space 3}0.147{col 59}{space 4}-.0139944{col 72}{space 3} .0932174
{txt}{space 4}houseexpend_z {c |}{col 19}{res}{space 2}  .083984{col 31}{space 2} .0589517{col 42}{space 1}    1.42{col 51}{space 3}0.155{col 59}{space 4}-.0318544{col 72}{space 3} .1998223
{txt}{space 5}assetindex_z {c |}{col 19}{res}{space 2} .0141037{col 31}{space 2} .0532986{col 42}{space 1}    0.26{col 51}{space 3}0.791{col 59}{space 4}-.0906264{col 72}{space 3} .1188338
{txt}{space 7}headh_miss {c |}{col 19}{res}{space 2} .0017303{col 31}{space 2} .0892043{col 42}{space 1}    0.02{col 51}{space 3}0.985{col 59}{space 4}-.1735534{col 72}{space 3} .1770141
{txt}{space 9}age_miss {c |}{col 19}{res}{space 2} .2266879{col 31}{space 2} .0748483{col 42}{space 1}    3.03{col 51}{space 3}0.003{col 59}{space 4} .0796131{col 72}{space 3} .3737626
{txt}{space 8}read_miss {c |}{col 19}{res}{space 2}-.0014916{col 31}{space 2} .0460358{col 42}{space 1}   -0.03{col 51}{space 3}0.974{col 59}{space 4}-.0919506{col 72}{space 3} .0889673
{txt}{space 8}math_miss {c |}{col 19}{res}{space 2} .0922755{col 31}{space 2} .0235203{col 42}{space 1}    3.92{col 51}{space 3}0.000{col 59}{space 4} .0460588{col 72}{space 3} .1384922
{txt}{space 8}educ_miss {c |}{col 19}{res}{space 2}  .139418{col 31}{space 2} .1010046{col 42}{space 1}    1.38{col 51}{space 3}0.168{col 59}{space 4}-.0590532{col 72}{space 3} .3378891
{txt}{space 1}houseexpend_miss {c |}{col 19}{res}{space 2} .0483921{col 31}{space 2} .0240352{col 42}{space 1}    2.01{col 51}{space 3}0.045{col 59}{space 4} .0011636{col 72}{space 3} .0956207
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5153902{col 31}{space 2} .0387645{col 42}{space 1}   13.30{col 51}{space 3}0.000{col 59}{space 4} .4392191{col 72}{space 3} .5915612
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F(  3,   483) ={res}    1.25
                                                       {txt}Prob > F      = {res} 0.2922
                                                       {txt}R-squared     = {res} 0.0035
                                                       {txt}Root MSE      = {res} .25346

{txt}{ralign 83:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}    policy_pref_d{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_d {c |}{col 19}{res}{space 2} .0255902{col 31}{space 2} .0567064{col 42}{space 1}    0.45{col 51}{space 3}0.652{col 59}{space 4}-.0858315{col 72}{space 3} .1370119
{txt}{space 8}knowledge {c |}{col 19}{res}{space 2} .0933567{col 31}{space 2} .0543944{col 42}{space 1}    1.72{col 51}{space 3}0.087{col 59}{space 4}-.0135221{col 72}{space 3} .2002356
{txt}knowledge_treat_d {c |}{col 19}{res}{space 2}-.0748993{col 31}{space 2} .0938861{col 42}{space 1}   -0.80{col 51}{space 3}0.425{col 59}{space 4} -.259375{col 72}{space 3} .1095764
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5809209{col 31}{space 2} .0324657{col 42}{space 1}   17.89{col 51}{space 3}0.000{col 59}{space 4} .5171295{col 72}{space 3} .6447122
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F( 17,   483) ={res}    4.51
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0443
                                                       {txt}Root MSE      = {res} .24855

{txt}{ralign 83:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}    policy_pref_d{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_d {c |}{col 19}{res}{space 2} .0221194{col 31}{space 2} .0546447{col 42}{space 1}    0.40{col 51}{space 3}0.686{col 59}{space 4}-.0852512{col 72}{space 3} .1294901
{txt}{space 8}knowledge {c |}{col 19}{res}{space 2} .0214426{col 31}{space 2} .0537052{col 42}{space 1}    0.40{col 51}{space 3}0.690{col 59}{space 4}-.0840821{col 72}{space 3} .1269673
{txt}knowledge_treat_d {c |}{col 19}{res}{space 2} -.074194{col 31}{space 2} .0896914{col 42}{space 1}   -0.83{col 51}{space 3}0.409{col 59}{space 4}-.2504275{col 72}{space 3} .1020395
{txt}{space 9}gender_z {c |}{col 19}{res}{space 2} .0234549{col 31}{space 2} .0196806{col 42}{space 1}    1.19{col 51}{space 3}0.234{col 59}{space 4}-.0152152{col 72}{space 3} .0621249
{txt}{space 10}headh_z {c |}{col 19}{res}{space 2} -.003484{col 31}{space 2} .0144814{col 42}{space 1}   -0.24{col 51}{space 3}0.810{col 59}{space 4}-.0319383{col 72}{space 3} .0249704
{txt}{space 12}age_z {c |}{col 19}{res}{space 2} .0306687{col 31}{space 2}  .032495{col 42}{space 1}    0.94{col 51}{space 3}0.346{col 59}{space 4}-.0331804{col 72}{space 3} .0945178
{txt}{space 11}read_z {c |}{col 19}{res}{space 2}-.0107751{col 31}{space 2} .0166356{col 42}{space 1}   -0.65{col 51}{space 3}0.517{col 59}{space 4}-.0434621{col 72}{space 3} .0219119
{txt}{space 11}math_z {c |}{col 19}{res}{space 2} .0790563{col 31}{space 2} .0197623{col 42}{space 1}    4.00{col 51}{space 3}0.000{col 59}{space 4} .0402256{col 72}{space 3}  .117887
{txt}{space 11}educ_z {c |}{col 19}{res}{space 2} .0522801{col 31}{space 2}  .026474{col 42}{space 1}    1.97{col 51}{space 3}0.049{col 59}{space 4} .0002617{col 72}{space 3} .1042985
{txt}{space 4}houseexpend_z {c |}{col 19}{res}{space 2} .2335987{col 31}{space 2} .0579305{col 42}{space 1}    4.03{col 51}{space 3}0.000{col 59}{space 4} .1197718{col 72}{space 3} .3474257
{txt}{space 5}assetindex_z {c |}{col 19}{res}{space 2}-.0527116{col 31}{space 2}  .052796{col 42}{space 1}   -1.00{col 51}{space 3}0.319{col 59}{space 4}-.1564499{col 72}{space 3} .0510267
{txt}{space 7}headh_miss {c |}{col 19}{res}{space 2}-.0725036{col 31}{space 2} .0842324{col 42}{space 1}   -0.86{col 51}{space 3}0.390{col 59}{space 4}-.2380108{col 72}{space 3} .0930036
{txt}{space 9}age_miss {c |}{col 19}{res}{space 2} .1045988{col 31}{space 2} .0871379{col 42}{space 1}    1.20{col 51}{space 3}0.231{col 59}{space 4}-.0666173{col 72}{space 3}  .275815
{txt}{space 8}read_miss {c |}{col 19}{res}{space 2}-.0877632{col 31}{space 2} .0571523{col 42}{space 1}   -1.54{col 51}{space 3}0.125{col 59}{space 4}-.2000611{col 72}{space 3} .0245347
{txt}{space 8}math_miss {c |}{col 19}{res}{space 2} .1075955{col 31}{space 2} .0258847{col 42}{space 1}    4.16{col 51}{space 3}0.000{col 59}{space 4}  .056735{col 72}{space 3} .1584559
{txt}{space 8}educ_miss {c |}{col 19}{res}{space 2} .1491179{col 31}{space 2} .0828062{col 42}{space 1}    1.80{col 51}{space 3}0.072{col 59}{space 4}-.0135871{col 72}{space 3} .3118228
{txt}{space 1}houseexpend_miss {c |}{col 19}{res}{space 2} .0767407{col 31}{space 2} .0255598{col 42}{space 1}    3.00{col 51}{space 3}0.003{col 59}{space 4} .0265186{col 72}{space 3} .1269628
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5170779{col 31}{space 2} .0386483{col 42}{space 1}   13.38{col 51}{space 3}0.000{col 59}{space 4} .4411383{col 72}{space 3} .5930175
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F(  3,   490) ={res}    2.32
                                                       {txt}Prob > F      = {res} 0.0741
                                                       {txt}R-squared     = {res} 0.0065
                                                       {txt}Root MSE      = {res} .23598

{txt}{ralign 83:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}    policy_pref_e{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_e {c |}{col 19}{res}{space 2} .0038793{col 31}{space 2} .0489213{col 42}{space 1}    0.08{col 51}{space 3}0.937{col 59}{space 4}-.0922422{col 72}{space 3} .1000008
{txt}{space 8}knowledge {c |}{col 19}{res}{space 2} .0933567{col 31}{space 2} .0543931{col 42}{space 1}    1.72{col 51}{space 3}0.087{col 59}{space 4}-.0135157{col 72}{space 3} .2002292
{txt}knowledge_treat_e {c |}{col 19}{res}{space 2} .0184062{col 31}{space 2} .0826542{col 42}{space 1}    0.22{col 51}{space 3}0.824{col 59}{space 4}-.1439942{col 72}{space 3} .1808067
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5809209{col 31}{space 2} .0324649{col 42}{space 1}   17.89{col 51}{space 3}0.000{col 59}{space 4} .5171333{col 72}{space 3} .6447084
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F( 17,   490) ={res}    4.28
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0452
                                                       {txt}Root MSE      = {res} .23164

{txt}{ralign 83:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}    policy_pref_e{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}treat_e {c |}{col 19}{res}{space 2} .0159453{col 31}{space 2} .0478116{col 42}{space 1}    0.33{col 51}{space 3}0.739{col 59}{space 4}-.0779958{col 72}{space 3} .1098863
{txt}{space 8}knowledge {c |}{col 19}{res}{space 2} .0209971{col 31}{space 2} .0532312{col 42}{space 1}    0.39{col 51}{space 3}0.693{col 59}{space 4}-.0835924{col 72}{space 3} .1255866
{txt}knowledge_treat_e {c |}{col 19}{res}{space 2}-.0091251{col 31}{space 2} .0805933{col 42}{space 1}   -0.11{col 51}{space 3}0.910{col 59}{space 4}-.1674761{col 72}{space 3} .1492259
{txt}{space 9}gender_z {c |}{col 19}{res}{space 2}  .037933{col 31}{space 2} .0174714{col 42}{space 1}    2.17{col 51}{space 3}0.030{col 59}{space 4} .0036049{col 72}{space 3} .0722612
{txt}{space 10}headh_z {c |}{col 19}{res}{space 2}-.0070982{col 31}{space 2} .0123797{col 42}{space 1}   -0.57{col 51}{space 3}0.567{col 59}{space 4}-.0314221{col 72}{space 3} .0172257
{txt}{space 12}age_z {c |}{col 19}{res}{space 2} .0037592{col 31}{space 2} .0304506{col 42}{space 1}    0.12{col 51}{space 3}0.902{col 59}{space 4}-.0560706{col 72}{space 3}  .063589
{txt}{space 11}read_z {c |}{col 19}{res}{space 2}-.0020595{col 31}{space 2} .0154806{col 42}{space 1}   -0.13{col 51}{space 3}0.894{col 59}{space 4} -.032476{col 72}{space 3}  .028357
{txt}{space 11}math_z {c |}{col 19}{res}{space 2}  .075562{col 31}{space 2} .0172816{col 42}{space 1}    4.37{col 51}{space 3}0.000{col 59}{space 4} .0416069{col 72}{space 3} .1095171
{txt}{space 11}educ_z {c |}{col 19}{res}{space 2} .0316334{col 31}{space 2}  .025237{col 42}{space 1}    1.25{col 51}{space 3}0.211{col 59}{space 4}-.0179528{col 72}{space 3} .0812195
{txt}{space 4}houseexpend_z {c |}{col 19}{res}{space 2} .0906462{col 31}{space 2} .0521165{col 42}{space 1}    1.74{col 51}{space 3}0.083{col 59}{space 4}-.0117532{col 72}{space 3} .1930456
{txt}{space 5}assetindex_z {c |}{col 19}{res}{space 2}-.0172511{col 31}{space 2} .0475403{col 42}{space 1}   -0.36{col 51}{space 3}0.717{col 59}{space 4}-.1106591{col 72}{space 3} .0761568
{txt}{space 7}headh_miss {c |}{col 19}{res}{space 2} .0640319{col 31}{space 2} .0513906{col 42}{space 1}    1.25{col 51}{space 3}0.213{col 59}{space 4}-.0369412{col 72}{space 3}  .165005
{txt}{space 9}age_miss {c |}{col 19}{res}{space 2} .0056248{col 31}{space 2} .0691201{col 42}{space 1}    0.08{col 51}{space 3}0.935{col 59}{space 4}-.1301836{col 72}{space 3} .1414332
{txt}{space 8}read_miss {c |}{col 19}{res}{space 2}-.0126848{col 31}{space 2} .0487685{col 42}{space 1}   -0.26{col 51}{space 3}0.795{col 59}{space 4}-.1085061{col 72}{space 3} .0831365
{txt}{space 8}math_miss {c |}{col 19}{res}{space 2} .0833188{col 31}{space 2} .0247831{col 42}{space 1}    3.36{col 51}{space 3}0.001{col 59}{space 4} .0346245{col 72}{space 3}  .132013
{txt}{space 8}educ_miss {c |}{col 19}{res}{space 2}-.1987507{col 31}{space 2} .0607835{col 42}{space 1}   -3.27{col 51}{space 3}0.001{col 59}{space 4}-.3181792{col 72}{space 3}-.0793222
{txt}{space 1}houseexpend_miss {c |}{col 19}{res}{space 2} .0515661{col 31}{space 2} .0231912{col 42}{space 1}    2.22{col 51}{space 3}0.027{col 59}{space 4} .0059997{col 72}{space 3} .0971325
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5306851{col 31}{space 2} .0368627{col 42}{space 1}   14.40{col 51}{space 3}0.000{col 59}{space 4} .4582565{col 72}{space 3} .6031137
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. // Third Panel - Endorsement condition interacted with policy-specific knowledge
.         
.         local group "militancy b c d e"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' k_scale k_treat_`x', cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' k_scale k_treat_`x' *_z *_miss, cluster(psu_new)  
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}   35.14
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0485
                                                       {txt}Root MSE      = {res} .24888

{txt}{ralign 83:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}policy_pref_mil~y{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}treat_militancy {c |}{col 19}{res}{space 2}-.0284842{col 31}{space 2} .0213524{col 42}{space 1}   -1.33{col 51}{space 3}0.183{col 59}{space 4}-.0703875{col 72}{space 3} .0134191
{txt}{space 10}k_scale {c |}{col 19}{res}{space 2} .1359482{col 31}{space 2} .0254484{col 42}{space 1}    5.34{col 51}{space 3}0.000{col 59}{space 4} .0860067{col 72}{space 3} .1858896
{txt}k_treat_militancy {c |}{col 19}{res}{space 2} .0225623{col 31}{space 2} .0312461{col 42}{space 1}    0.72{col 51}{space 3}0.470{col 59}{space 4}-.0387569{col 72}{space 3} .0838814
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5714722{col 31}{space 2} .0171717{col 42}{space 1}   33.28{col 51}{space 3}0.000{col 59}{space 4} .5377734{col 72}{space 3}  .605171
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 17,   952) ={res}   10.60
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0664
                                                       {txt}Root MSE      = {res} .24669

{txt}{ralign 83:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 18}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 19}{c |}{col 31}    Robust
{col 1}policy_pref_mil~y{col 19}{c |}      Coef.{col 31}   Std. Err.{col 43}      t{col 51}   P>|t|{col 59}     [95% Con{col 72}f. Interval]
{hline 18}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 2}treat_militancy {c |}{col 19}{res}{space 2}-.0311313{col 31}{space 2}  .020986{col 42}{space 1}   -1.48{col 51}{space 3}0.138{col 59}{space 4}-.0723155{col 72}{space 3} .0100529
{txt}{space 10}k_scale {c |}{col 19}{res}{space 2} .1179975{col 31}{space 2} .0257819{col 42}{space 1}    4.58{col 51}{space 3}0.000{col 59}{space 4} .0674015{col 72}{space 3} .1685935
{txt}k_treat_militancy {c |}{col 19}{res}{space 2}  .020569{col 31}{space 2} .0309744{col 42}{space 1}    0.66{col 51}{space 3}0.507{col 59}{space 4}-.0402171{col 72}{space 3}  .081355
{txt}{space 9}gender_z {c |}{col 19}{res}{space 2} .0124837{col 31}{space 2} .0136975{col 42}{space 1}    0.91{col 51}{space 3}0.362{col 59}{space 4}-.0143971{col 72}{space 3} .0393644
{txt}{space 10}headh_z {c |}{col 19}{res}{space 2}-.0033317{col 31}{space 2} .0093389{col 42}{space 1}   -0.36{col 51}{space 3}0.721{col 59}{space 4}-.0216589{col 72}{space 3} .0149955
{txt}{space 12}age_z {c |}{col 19}{res}{space 2} .0186209{col 31}{space 2} .0212031{col 42}{space 1}    0.88{col 51}{space 3}0.380{col 59}{space 4}-.0229892{col 72}{space 3}  .060231
{txt}{space 11}read_z {c |}{col 19}{res}{space 2}-.0218437{col 31}{space 2} .0118696{col 42}{space 1}   -1.84{col 51}{space 3}0.066{col 59}{space 4}-.0451373{col 72}{space 3} .0014499
{txt}{space 11}math_z {c |}{col 19}{res}{space 2} .0492611{col 31}{space 2} .0135635{col 42}{space 1}    3.63{col 51}{space 3}0.000{col 59}{space 4} .0226433{col 72}{space 3}  .075879
{txt}{space 11}educ_z {c |}{col 19}{res}{space 2} .0332237{col 31}{space 2} .0192792{col 42}{space 1}    1.72{col 51}{space 3}0.085{col 59}{space 4} -.004611{col 72}{space 3} .0710585
{txt}{space 4}houseexpend_z {c |}{col 19}{res}{space 2}  .179659{col 31}{space 2} .0402722{col 42}{space 1}    4.46{col 51}{space 3}0.000{col 59}{space 4} .1006265{col 72}{space 3} .2586915
{txt}{space 5}assetindex_z {c |}{col 19}{res}{space 2}-.0771446{col 31}{space 2} .0363643{col 42}{space 1}   -2.12{col 51}{space 3}0.034{col 59}{space 4}-.1485081{col 72}{space 3}-.0057811
{txt}{space 7}headh_miss {c |}{col 19}{res}{space 2}-.0363846{col 31}{space 2} .0478131{col 42}{space 1}   -0.76{col 51}{space 3}0.447{col 59}{space 4}-.1302159{col 72}{space 3} .0574467
{txt}{space 9}age_miss {c |}{col 19}{res}{space 2} .1716735{col 31}{space 2} .0541584{col 42}{space 1}    3.17{col 51}{space 3}0.002{col 59}{space 4} .0653898{col 72}{space 3} .2779571
{txt}{space 8}read_miss {c |}{col 19}{res}{space 2}-.0795022{col 31}{space 2} .0394951{col 42}{space 1}   -2.01{col 51}{space 3}0.044{col 59}{space 4}-.1570098{col 72}{space 3}-.0019946
{txt}{space 8}math_miss {c |}{col 19}{res}{space 2} .0752702{col 31}{space 2}  .016816{col 42}{space 1}    4.48{col 51}{space 3}0.000{col 59}{space 4} .0422694{col 72}{space 3}  .108271
{txt}{space 8}educ_miss {c |}{col 19}{res}{space 2} .1224857{col 31}{space 2} .0573552{col 42}{space 1}    2.14{col 51}{space 3}0.033{col 59}{space 4} .0099284{col 72}{space 3}  .235043
{txt}{space 1}houseexpend_miss {c |}{col 19}{res}{space 2} .0678412{col 31}{space 2} .0181918{col 42}{space 1}    3.73{col 51}{space 3}0.000{col 59}{space 4} .0321406{col 72}{space 3} .1035419
{txt}{space 12}_cons {c |}{col 19}{res}{space 2} .5376645{col 31}{space 2} .0253797{col 42}{space 1}   21.18{col 51}{space 3}0.000{col 59}{space 4} .4878579{col 72}{space 3} .5874712
{txt}{hline 18}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F(  3,   474) ={res}   18.05
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0457
                                                       {txt}Root MSE      = {res} .23933

{txt}{ralign 78:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~b{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_b {c |}{col 14}{res}{space 2}-.0194539{col 26}{space 2} .0271819{col 37}{space 1}   -0.72{col 46}{space 3}0.475{col 54}{space 4}-.0728657{col 67}{space 3}  .033958
{txt}{space 5}k_scale {c |}{col 14}{res}{space 2} .1359482{col 26}{space 2} .0254655{col 37}{space 1}    5.34{col 46}{space 3}0.000{col 54}{space 4}  .085909{col 67}{space 3} .1859873
{txt}{space 3}k_treat_b {c |}{col 14}{res}{space 2} .0159717{col 26}{space 2} .0393744{col 37}{space 1}    0.41{col 46}{space 3}0.685{col 54}{space 4}-.0613983{col 67}{space 3} .0933417
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5714722{col 26}{space 2} .0171832{col 37}{space 1}   33.26{col 46}{space 3}0.000{col 54}{space 4} .5377074{col 67}{space 3} .6052369
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F( 17,   474) ={res}    5.71
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0621
                                                       {txt}Root MSE      = {res} .23758

{txt}{ralign 82:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_b{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_b {c |}{col 18}{res}{space 2}-.0187785{col 30}{space 2} .0267164{col 41}{space 1}   -0.70{col 50}{space 3}0.482{col 58}{space 4}-.0712757{col 71}{space 3} .0337187
{txt}{space 9}k_scale {c |}{col 18}{res}{space 2} .1221559{col 30}{space 2} .0262552{col 41}{space 1}    4.65{col 50}{space 3}0.000{col 58}{space 4}  .070565{col 71}{space 3} .1737469
{txt}{space 7}k_treat_b {c |}{col 18}{res}{space 2} .0108277{col 30}{space 2} .0390076{col 41}{space 1}    0.28{col 50}{space 3}0.781{col 58}{space 4}-.0658215{col 71}{space 3} .0874769
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0026391{col 30}{space 2} .0175395{col 41}{space 1}    0.15{col 50}{space 3}0.880{col 58}{space 4}-.0318257{col 71}{space 3} .0371039
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2} .0141115{col 30}{space 2} .0124702{col 41}{space 1}    1.13{col 50}{space 3}0.258{col 58}{space 4}-.0103923{col 71}{space 3} .0386152
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0096006{col 30}{space 2} .0287017{col 41}{space 1}    0.33{col 50}{space 3}0.738{col 58}{space 4}-.0467978{col 71}{space 3} .0659989
{txt}{space 10}read_z {c |}{col 18}{res}{space 2}-.0422542{col 30}{space 2}  .015189{col 41}{space 1}   -2.78{col 50}{space 3}0.006{col 58}{space 4}-.0721003{col 71}{space 3}-.0124082
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0579497{col 30}{space 2} .0164368{col 41}{space 1}    3.53{col 50}{space 3}0.000{col 58}{space 4} .0256517{col 71}{space 3} .0902478
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0471686{col 30}{space 2} .0237735{col 41}{space 1}    1.98{col 50}{space 3}0.048{col 58}{space 4} .0004542{col 71}{space 3}  .093883
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .0969599{col 30}{space 2} .0569314{col 41}{space 1}    1.70{col 50}{space 3}0.089{col 58}{space 4}-.0149092{col 71}{space 3}  .208829
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0205837{col 30}{space 2} .0479623{col 41}{space 1}   -0.43{col 50}{space 3}0.668{col 58}{space 4}-.1148287{col 71}{space 3} .0736612
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2} .0105634{col 30}{space 2}  .053259{col 41}{space 1}    0.20{col 50}{space 3}0.843{col 58}{space 4}-.0940897{col 71}{space 3} .1152164
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .1991165{col 30}{space 2} .0571126{col 41}{space 1}    3.49{col 50}{space 3}0.001{col 58}{space 4} .0868914{col 71}{space 3} .3113417
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0849015{col 30}{space 2} .0624561{col 41}{space 1}   -1.36{col 50}{space 3}0.175{col 58}{space 4}-.2076265{col 71}{space 3} .0378236
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0867296{col 30}{space 2} .0200618{col 41}{space 1}    4.32{col 50}{space 3}0.000{col 58}{space 4} .0473085{col 71}{space 3} .1261506
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2} .0342264{col 30}{space 2} .0645156{col 41}{space 1}    0.53{col 50}{space 3}0.596{col 58}{space 4}-.0925456{col 71}{space 3} .1609984
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0560904{col 30}{space 2} .0229515{col 41}{space 1}    2.44{col 50}{space 3}0.015{col 58}{space 4} .0109911{col 71}{space 3} .1011897
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5233422{col 30}{space 2} .0306293{col 41}{space 1}   17.09{col 50}{space 3}0.000{col 58}{space 4} .4631561{col 71}{space 3} .5835283
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F(  3,   475) ={res}   20.67
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0538
                                                       {txt}Root MSE      = {res} .23866

{txt}{ralign 78:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~c{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_c {c |}{col 14}{res}{space 2}-.0363606{col 26}{space 2} .0273145{col 37}{space 1}   -1.33{col 46}{space 3}0.184{col 54}{space 4}-.0900328{col 67}{space 3} .0173116
{txt}{space 5}k_scale {c |}{col 14}{res}{space 2} .1359482{col 26}{space 2} .0254655{col 37}{space 1}    5.34{col 46}{space 3}0.000{col 54}{space 4} .0859093{col 67}{space 3} .1859871
{txt}{space 3}k_treat_c {c |}{col 14}{res}{space 2} .0354825{col 26}{space 2} .0391338{col 37}{space 1}    0.91{col 46}{space 3}0.365{col 54}{space 4}-.0414143{col 67}{space 3} .1123793
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5714722{col 26}{space 2} .0171832{col 37}{space 1}   33.26{col 46}{space 3}0.000{col 54}{space 4} .5377076{col 67}{space 3} .6052367
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F( 17,   475) ={res}    6.33
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0683
                                                       {txt}Root MSE      = {res} .23714

{txt}{ralign 82:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_c{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_c {c |}{col 18}{res}{space 2}  -.04032{col 30}{space 2}  .026746{col 41}{space 1}   -1.51{col 50}{space 3}0.132{col 58}{space 4}-.0928751{col 71}{space 3} .0122351
{txt}{space 9}k_scale {c |}{col 18}{res}{space 2} .1196283{col 30}{space 2} .0263206{col 41}{space 1}    4.55{col 50}{space 3}0.000{col 58}{space 4} .0679091{col 71}{space 3} .1713474
{txt}{space 7}k_treat_c {c |}{col 18}{res}{space 2} .0349691{col 30}{space 2} .0389999{col 41}{space 1}    0.90{col 50}{space 3}0.370{col 58}{space 4}-.0416646{col 71}{space 3} .1116028
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0201953{col 30}{space 2} .0182331{col 41}{space 1}    1.11{col 50}{space 3}0.269{col 58}{space 4}-.0156323{col 71}{space 3} .0560229
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0219702{col 30}{space 2} .0124741{col 41}{space 1}   -1.76{col 50}{space 3}0.079{col 58}{space 4}-.0464814{col 71}{space 3} .0025411
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0236916{col 30}{space 2} .0293449{col 41}{space 1}    0.81{col 50}{space 3}0.420{col 58}{space 4}-.0339702{col 71}{space 3} .0813534
{txt}{space 10}read_z {c |}{col 18}{res}{space 2} .0013356{col 30}{space 2} .0162234{col 41}{space 1}    0.08{col 50}{space 3}0.934{col 58}{space 4}-.0305428{col 71}{space 3} .0332141
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0416973{col 30}{space 2} .0184853{col 41}{space 1}    2.26{col 50}{space 3}0.025{col 58}{space 4} .0053743{col 71}{space 3} .0780203
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0161859{col 30}{space 2} .0266597{col 41}{space 1}    0.61{col 50}{space 3}0.544{col 58}{space 4}-.0361996{col 71}{space 3} .0685715
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .0289607{col 30}{space 2} .0556297{col 41}{space 1}    0.52{col 50}{space 3}0.603{col 58}{space 4}-.0803501{col 71}{space 3} .1382715
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0052646{col 30}{space 2} .0519895{col 41}{space 1}   -0.10{col 50}{space 3}0.919{col 58}{space 4}-.1074224{col 71}{space 3} .0968933
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}-.0187751{col 30}{space 2} .0894301{col 41}{space 1}   -0.21{col 50}{space 3}0.834{col 58}{space 4}-.1945027{col 71}{space 3} .1569524
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .2109377{col 30}{space 2}  .079704{col 41}{space 1}    2.65{col 50}{space 3}0.008{col 58}{space 4} .0543217{col 71}{space 3} .3675537
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0020175{col 30}{space 2} .0417671{col 41}{space 1}   -0.05{col 50}{space 3}0.961{col 58}{space 4}-.0840886{col 71}{space 3} .0800535
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0841732{col 30}{space 2} .0227759{col 41}{space 1}    3.70{col 50}{space 3}0.000{col 58}{space 4} .0394193{col 71}{space 3} .1289271
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2} .1449547{col 30}{space 2} .0989643{col 41}{space 1}    1.46{col 50}{space 3}0.144{col 58}{space 4}-.0495073{col 71}{space 3} .3394168
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0436246{col 30}{space 2}   .02435{col 41}{space 1}    1.79{col 50}{space 3}0.074{col 58}{space 4}-.0042225{col 71}{space 3} .0914716
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5272837{col 30}{space 2} .0316876{col 41}{space 1}   16.64{col 50}{space 3}0.000{col 58}{space 4} .4650185{col 71}{space 3} .5895488
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F(  3,   483) ={res}   16.21
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0437
                                                       {txt}Root MSE      = {res}  .2483

{txt}{ralign 78:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~d{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_d {c |}{col 14}{res}{space 2}-.0289884{col 26}{space 2} .0288617{col 37}{space 1}   -1.00{col 46}{space 3}0.316{col 54}{space 4}-.0856983{col 67}{space 3} .0277216
{txt}{space 5}k_scale {c |}{col 14}{res}{space 2} .1359482{col 26}{space 2} .0254651{col 37}{space 1}    5.34{col 46}{space 3}0.000{col 54}{space 4} .0859122{col 67}{space 3} .1859842
{txt}{space 3}k_treat_d {c |}{col 14}{res}{space 2} .0141766{col 26}{space 2} .0426631{col 37}{space 1}    0.33{col 46}{space 3}0.740{col 54}{space 4}-.0696516{col 67}{space 3} .0980048
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5714722{col 26}{space 2}  .017183{col 37}{space 1}   33.26{col 46}{space 3}0.000{col 54}{space 4} .5377096{col 67}{space 3} .6052348
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F( 17,   483) ={res}    5.72
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0676
                                                       {txt}Root MSE      = {res} .24551

{txt}{ralign 82:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_d{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_d {c |}{col 18}{res}{space 2}-.0307679{col 30}{space 2} .0281067{col 41}{space 1}   -1.09{col 50}{space 3}0.274{col 58}{space 4}-.0859944{col 71}{space 3} .0244586
{txt}{space 9}k_scale {c |}{col 18}{res}{space 2} .1121708{col 30}{space 2} .0262432{col 41}{space 1}    4.27{col 50}{space 3}0.000{col 58}{space 4} .0606059{col 71}{space 3} .1637357
{txt}{space 7}k_treat_d {c |}{col 18}{res}{space 2} .0105462{col 30}{space 2}   .04168{col 41}{space 1}    0.25{col 50}{space 3}0.800{col 58}{space 4}-.0713504{col 71}{space 3} .0924427
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0105071{col 30}{space 2} .0192353{col 41}{space 1}    0.55{col 50}{space 3}0.585{col 58}{space 4}-.0272881{col 71}{space 3} .0483022
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0039586{col 30}{space 2} .0141028{col 41}{space 1}   -0.28{col 50}{space 3}0.779{col 58}{space 4} -.031669{col 71}{space 3} .0237518
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0244083{col 30}{space 2} .0315835{col 41}{space 1}    0.77{col 50}{space 3}0.440{col 58}{space 4}-.0376498{col 71}{space 3} .0864664
{txt}{space 10}read_z {c |}{col 18}{res}{space 2}-.0137027{col 30}{space 2} .0164526{col 41}{space 1}   -0.83{col 50}{space 3}0.405{col 58}{space 4}-.0460302{col 71}{space 3} .0186248
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0651002{col 30}{space 2}  .019468{col 41}{space 1}    3.34{col 50}{space 3}0.001{col 58}{space 4} .0268477{col 71}{space 3} .1033527
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0337909{col 30}{space 2} .0263477{col 41}{space 1}    1.28{col 50}{space 3}0.200{col 58}{space 4}-.0179793{col 71}{space 3} .0855611
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .1839974{col 30}{space 2} .0559491{col 41}{space 1}    3.29{col 50}{space 3}0.001{col 58}{space 4} .0740637{col 71}{space 3} .2939311
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0855887{col 30}{space 2} .0505822{col 41}{space 1}   -1.69{col 50}{space 3}0.091{col 58}{space 4} -.184977{col 71}{space 3} .0137997
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}-.0729903{col 30}{space 2} .0804428{col 41}{space 1}   -0.91{col 50}{space 3}0.365{col 58}{space 4}-.2310515{col 71}{space 3} .0850708
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .0984741{col 30}{space 2} .0926712{col 41}{space 1}    1.06{col 50}{space 3}0.288{col 58}{space 4}-.0836144{col 71}{space 3} .2805626
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0689504{col 30}{space 2} .0597355{col 41}{space 1}   -1.15{col 50}{space 3}0.249{col 58}{space 4}-.1863239{col 71}{space 3}  .048423
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .1033464{col 30}{space 2} .0253803{col 41}{space 1}    4.07{col 50}{space 3}0.000{col 58}{space 4} .0534771{col 71}{space 3} .1532158
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2}  .133499{col 30}{space 2} .0850645{col 41}{space 1}    1.57{col 50}{space 3}0.117{col 58}{space 4}-.0336432{col 71}{space 3} .3006412
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0713961{col 30}{space 2} .0251713{col 41}{space 1}    2.84{col 50}{space 3}0.005{col 58}{space 4} .0219372{col 71}{space 3} .1208549
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5261923{col 30}{space 2} .0311861{col 41}{space 1}   16.87{col 50}{space 3}0.000{col 58}{space 4} .4649151{col 71}{space 3} .5874695
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F(  3,   490) ={res}   18.47
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0480
                                                       {txt}Root MSE      = {res}   .231

{txt}{ralign 78:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_e {c |}{col 14}{res}{space 2} .0066257{col 26}{space 2} .0251321{col 37}{space 1}    0.26{col 46}{space 3}0.792{col 54}{space 4}-.0427543{col 67}{space 3} .0560056
{txt}{space 5}k_scale {c |}{col 14}{res}{space 2} .1359482{col 26}{space 2} .0254645{col 37}{space 1}    5.34{col 46}{space 3}0.000{col 54}{space 4} .0859152{col 67}{space 3} .1859812
{txt}{space 3}k_treat_e {c |}{col 14}{res}{space 2} .0031105{col 26}{space 2} .0371481{col 37}{space 1}    0.08{col 46}{space 3}0.933{col 54}{space 4}-.0698787{col 67}{space 3} .0760997
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .5714722{col 26}{space 2} .0171826{col 37}{space 1}   33.26{col 46}{space 3}0.000{col 54}{space 4} .5377116{col 67}{space 3} .6052328
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F( 17,   490) ={res}    6.09
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0708
                                                       {txt}Root MSE      = {res} .22851

{txt}{ralign 82:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_e {c |}{col 18}{res}{space 2}  .010046{col 30}{space 2} .0242388{col 41}{space 1}    0.41{col 50}{space 3}0.679{col 58}{space 4}-.0375788{col 71}{space 3} .0576708
{txt}{space 9}k_scale {c |}{col 18}{res}{space 2} .1158411{col 30}{space 2}  .026113{col 41}{space 1}    4.44{col 50}{space 3}0.000{col 58}{space 4} .0645338{col 71}{space 3} .1671484
{txt}{space 7}k_treat_e {c |}{col 18}{res}{space 2}-.0072903{col 30}{space 2} .0357452{col 41}{space 1}   -0.20{col 50}{space 3}0.838{col 58}{space 4}-.0775231{col 71}{space 3} .0629424
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0257974{col 30}{space 2} .0173484{col 41}{space 1}    1.49{col 50}{space 3}0.138{col 58}{space 4}-.0082889{col 71}{space 3} .0598838
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0062327{col 30}{space 2} .0119797{col 41}{space 1}   -0.52{col 50}{space 3}0.603{col 58}{space 4}-.0297706{col 71}{space 3} .0173051
{txt}{space 11}age_z {c |}{col 18}{res}{space 2}-.0047299{col 30}{space 2} .0296934{col 41}{space 1}   -0.16{col 50}{space 3}0.874{col 58}{space 4}-.0630721{col 71}{space 3} .0536123
{txt}{space 10}read_z {c |}{col 18}{res}{space 2}-.0089757{col 30}{space 2} .0150633{col 41}{space 1}   -0.60{col 50}{space 3}0.552{col 58}{space 4}-.0385723{col 71}{space 3} .0206208
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0654393{col 30}{space 2} .0171195{col 41}{space 1}    3.82{col 50}{space 3}0.000{col 58}{space 4} .0318027{col 71}{space 3} .0990759
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0144646{col 30}{space 2} .0245854{col 41}{space 1}    0.59{col 50}{space 3}0.557{col 58}{space 4}-.0338413{col 71}{space 3} .0627704
{txt}{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .0572507{col 30}{space 2} .0500413{col 41}{space 1}    1.14{col 50}{space 3}0.253{col 58}{space 4}-.0410713{col 71}{space 3} .1555726
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0393064{col 30}{space 2} .0461278{col 41}{space 1}   -0.85{col 50}{space 3}0.395{col 58}{space 4}-.1299391{col 71}{space 3} .0513263
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2} .0729254{col 30}{space 2} .0507283{col 41}{space 1}    1.44{col 50}{space 3}0.151{col 58}{space 4}-.0267465{col 71}{space 3} .1725973
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2}-.0360356{col 30}{space 2}  .067307{col 41}{space 1}   -0.54{col 50}{space 3}0.593{col 58}{space 4}-.1682815{col 71}{space 3} .0962104
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2} .0102778{col 30}{space 2} .0480687{col 41}{space 1}    0.21{col 50}{space 3}0.831{col 58}{space 4}-.0841684{col 71}{space 3} .1047241
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0806192{col 30}{space 2} .0251344{col 41}{space 1}    3.21{col 50}{space 3}0.001{col 58}{space 4} .0312348{col 71}{space 3} .1300037
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2}-.1965906{col 30}{space 2} .0588248{col 41}{space 1}   -3.34{col 50}{space 3}0.001{col 58}{space 4}-.3121706{col 71}{space 3}-.0810106
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0538203{col 30}{space 2} .0229773{col 41}{space 1}    2.34{col 50}{space 3}0.020{col 58}{space 4} .0086741{col 71}{space 3} .0989664
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5276551{col 30}{space 2} .0291565{col 41}{space 1}   18.10{col 50}{space 3}0.000{col 58}{space 4} .4703678{col 71}{space 3} .5849423
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. // Fourth panel - Endorsement condition interacted with level of education
. 
.         local group "militancy b c d e"
{txt}
{com}.         foreach x of local group {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' educ_z educ_treat_`x' educ_miss, cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' educ_z educ_treat_`x' *_z *_miss, cluster(psu_new)        
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  4,   952) ={res}   11.30
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0129
                                                       {txt}Root MSE      = {res}  .2535

{txt}{ralign 86:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}policy_pref_milita~y{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      t{col 54}   P>|t|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_militancy {c |}{col 22}{res}{space 2}-.0089061{col 34}{space 2} .0177058{col 45}{space 1}   -0.50{col 54}{space 3}0.615{col 62}{space 4}-.0436531{col 75}{space 3} .0258409
{txt}{space 14}educ_z {c |}{col 22}{res}{space 2} .1054313{col 34}{space 2} .0245856{col 45}{space 1}    4.29{col 54}{space 3}0.000{col 62}{space 4} .0571831{col 75}{space 3} .1536795
{txt}educ_treat_militancy {c |}{col 22}{res}{space 2}-.0167783{col 34}{space 2} .0308428{col 45}{space 1}   -0.54{col 54}{space 3}0.587{col 62}{space 4} -.077306{col 75}{space 3} .0437495
{txt}{space 11}educ_miss {c |}{col 22}{res}{space 2} .1470846{col 34}{space 2} .0566762{col 45}{space 1}    2.60{col 54}{space 3}0.010{col 62}{space 4} .0358598{col 75}{space 3} .2583094
{txt}{space 15}_cons {c |}{col 22}{res}{space 2} .6095269{col 34}{space 2} .0143147{col 45}{space 1}   42.58{col 54}{space 3}0.000{col 62}{space 4} .5814348{col 75}{space 3}  .637619
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: educ_z omitted because of collinearity

Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 16,   952) ={res}    8.35
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0348
                                                       {txt}Root MSE      = {res} .25082

{txt}{ralign 86:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 21}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 22}{c |}{col 34}    Robust
{col 1}policy_pref_milita~y{col 22}{c |}      Coef.{col 34}   Std. Err.{col 46}      t{col 54}   P>|t|{col 62}     [95% Con{col 75}f. Interval]
{hline 21}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_militancy {c |}{col 22}{res}{space 2} -.011508{col 34}{space 2} .0173273{col 45}{space 1}   -0.66{col 54}{space 3}0.507{col 62}{space 4} -.045512{col 75}{space 3} .0224961
{txt}{space 14}educ_z {c |}{col 22}{res}{space 2} .0691853{col 34}{space 2} .0274464{col 45}{space 1}    2.52{col 54}{space 3}0.012{col 62}{space 4} .0153227{col 75}{space 3} .1230478
{txt}educ_treat_militancy {c |}{col 22}{res}{space 2}-.0176527{col 34}{space 2} .0302809{col 45}{space 1}   -0.58{col 54}{space 3}0.560{col 62}{space 4}-.0770778{col 75}{space 3} .0417724
{txt}{space 12}gender_z {c |}{col 22}{res}{space 2} .0261097{col 34}{space 2} .0136177{col 45}{space 1}    1.92{col 54}{space 3}0.055{col 62}{space 4}-.0006144{col 75}{space 3} .0528339
{txt}{space 13}headh_z {c |}{col 22}{res}{space 2}-.0042516{col 34}{space 2} .0094194{col 45}{space 1}   -0.45{col 54}{space 3}0.652{col 62}{space 4}-.0227368{col 75}{space 3} .0142336
{txt}{space 15}age_z {c |}{col 22}{res}{space 2} .0289421{col 34}{space 2} .0215701{col 45}{space 1}    1.34{col 54}{space 3}0.180{col 62}{space 4}-.0133885{col 75}{space 3} .0712726
{txt}{space 14}read_z {c |}{col 22}{res}{space 2}-.0202434{col 34}{space 2} .0121844{col 45}{space 1}   -1.66{col 54}{space 3}0.097{col 62}{space 4}-.0441547{col 75}{space 3}  .003668
{txt}{space 14}math_z {c |}{col 22}{res}{space 2}  .063792{col 34}{space 2} .0140298{col 45}{space 1}    4.55{col 54}{space 3}0.000{col 62}{space 4} .0362591{col 75}{space 3} .0913249
{txt}{space 14}educ_z {c |}{col 22}{res}{space 2}        0{col 34}{txt}  (omitted)
{space 7}houseexpend_z {c |}{col 22}{res}{space 2} .2330036{col 34}{space 2} .0417011{col 45}{space 1}    5.59{col 54}{space 3}0.000{col 62}{space 4} .1511669{col 75}{space 3} .3148403
{txt}{space 8}assetindex_z {c |}{col 22}{res}{space 2}-.0473573{col 34}{space 2} .0367113{col 45}{space 1}   -1.29{col 54}{space 3}0.197{col 62}{space 4}-.1194016{col 75}{space 3} .0246871
{txt}{space 10}headh_miss {c |}{col 22}{res}{space 2}-.0402571{col 34}{space 2} .0495839{col 45}{space 1}   -0.81{col 54}{space 3}0.417{col 62}{space 4}-.1375635{col 75}{space 3} .0570493
{txt}{space 12}age_miss {c |}{col 22}{res}{space 2} .1807747{col 34}{space 2} .0506881{col 45}{space 1}    3.57{col 54}{space 3}0.000{col 62}{space 4} .0813014{col 75}{space 3} .2802481
{txt}{space 11}read_miss {c |}{col 22}{res}{space 2}-.0805058{col 34}{space 2} .0398237{col 45}{space 1}   -2.02{col 54}{space 3}0.044{col 62}{space 4}-.1586582{col 75}{space 3}-.0023535
{txt}{space 11}math_miss {c |}{col 22}{res}{space 2} .0854848{col 34}{space 2} .0171899{col 45}{space 1}    4.97{col 54}{space 3}0.000{col 62}{space 4} .0517502{col 75}{space 3} .1192193
{txt}{space 11}educ_miss {c |}{col 22}{res}{space 2}  .126525{col 34}{space 2} .0578377{col 45}{space 1}    2.19{col 54}{space 3}0.029{col 62}{space 4}  .013021{col 75}{space 3} .2400291
{txt}{space 4}houseexpend_miss {c |}{col 22}{res}{space 2} .0762188{col 34}{space 2} .0182272{col 45}{space 1}    4.18{col 54}{space 3}0.000{col 62}{space 4} .0404487{col 75}{space 3} .1119889
{txt}{space 15}_cons {c |}{col 22}{res}{space 2}  .539743{col 34}{space 2} .0236569{col 45}{space 1}   22.82{col 54}{space 3}0.000{col 62}{space 4} .4933173{col 75}{space 3} .5861687
{txt}{hline 21}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F(  4,   474) ={res}    5.62
                                                       {txt}Prob > F      = {res} 0.0002
                                                       {txt}R-squared     = {res} 0.0104
                                                       {txt}Root MSE      = {res} .24374

{txt}{ralign 78:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~b{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_b {c |}{col 14}{res}{space 2} .0063695{col 26}{space 2} .0218552{col 37}{space 1}    0.29{col 46}{space 3}0.771{col 54}{space 4}-.0365756{col 67}{space 3} .0493146
{txt}{space 6}educ_z {c |}{col 14}{res}{space 2}  .104931{col 26}{space 2} .0246152{col 37}{space 1}    4.26{col 46}{space 3}0.000{col 54}{space 4} .0565626{col 67}{space 3} .1532993
{txt}educ_treat_b {c |}{col 14}{res}{space 2}-.0412966{col 26}{space 2} .0400193{col 37}{space 1}   -1.03{col 46}{space 3}0.303{col 54}{space 4}-.1199338{col 67}{space 3} .0373406
{txt}{space 3}educ_miss {c |}{col 14}{res}{space 2} .0457436{col 26}{space 2} .0653983{col 37}{space 1}    0.70{col 46}{space 3}0.485{col 54}{space 4}-.0827628{col 67}{space 3} .1742499
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6098145{col 26}{space 2} .0143364{col 37}{space 1}   42.54{col 46}{space 3}0.000{col 54}{space 4} .5816438{col 67}{space 3} .6379851
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: educ_z omitted because of collinearity

Linear regression                                      Number of obs ={res}    5286
                                                       {txt}F( 16,   474) ={res}    5.00
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0319
                                                       {txt}Root MSE      = {res} .24136

{txt}{ralign 82:(Std. Err. adjusted for {res:475} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_b{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_b {c |}{col 18}{res}{space 2} .0050151{col 30}{space 2} .0213363{col 41}{space 1}    0.24{col 50}{space 3}0.814{col 58}{space 4}-.0369104{col 71}{space 3} .0469406
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0925128{col 30}{space 2} .0296758{col 41}{space 1}    3.12{col 50}{space 3}0.002{col 58}{space 4} .0342004{col 71}{space 3} .1508253
{txt}{space 4}educ_treat_b {c |}{col 18}{res}{space 2}-.0437339{col 30}{space 2} .0395099{col 41}{space 1}   -1.11{col 50}{space 3}0.269{col 58}{space 4}-.1213701{col 71}{space 3} .0339023
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0161283{col 30}{space 2} .0176964{col 41}{space 1}    0.91{col 50}{space 3}0.363{col 58}{space 4}-.0186447{col 71}{space 3} .0509013
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2} .0102427{col 30}{space 2} .0127771{col 41}{space 1}    0.80{col 50}{space 3}0.423{col 58}{space 4}-.0148641{col 71}{space 3} .0353494
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0203953{col 30}{space 2}  .029515{col 41}{space 1}    0.69{col 50}{space 3}0.490{col 58}{space 4}-.0376011{col 71}{space 3} .0783918
{txt}{space 10}read_z {c |}{col 18}{res}{space 2} -.041014{col 30}{space 2} .0158106{col 41}{space 1}   -2.59{col 50}{space 3}0.010{col 58}{space 4}-.0720816{col 71}{space 3}-.0099464
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0716732{col 30}{space 2} .0168555{col 41}{space 1}    4.25{col 50}{space 3}0.000{col 58}{space 4} .0385525{col 71}{space 3} .1047939
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .1413012{col 30}{space 2} .0573148{col 41}{space 1}    2.47{col 50}{space 3}0.014{col 58}{space 4} .0286786{col 71}{space 3} .2539237
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}  .007381{col 30}{space 2}  .048895{col 41}{space 1}    0.15{col 50}{space 3}0.880{col 58}{space 4}-.0886969{col 71}{space 3} .1034588
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}-.0266328{col 30}{space 2} .0564838{col 41}{space 1}   -0.47{col 50}{space 3}0.637{col 58}{space 4}-.1376223{col 71}{space 3} .0843567
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .2083541{col 30}{space 2} .0511402{col 41}{space 1}    4.07{col 50}{space 3}0.000{col 58}{space 4} .1078646{col 71}{space 3} .3088435
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0948512{col 30}{space 2} .0603084{col 41}{space 1}   -1.57{col 50}{space 3}0.116{col 58}{space 4}-.2133562{col 71}{space 3} .0236537
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0914405{col 30}{space 2} .0206305{col 41}{space 1}    4.43{col 50}{space 3}0.000{col 58}{space 4} .0509019{col 71}{space 3} .1319792
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2} .0416182{col 30}{space 2} .0630905{col 41}{space 1}    0.66{col 50}{space 3}0.510{col 58}{space 4}-.0823535{col 71}{space 3}   .16559
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0578086{col 30}{space 2} .0227027{col 41}{space 1}    2.55{col 50}{space 3}0.011{col 58}{space 4} .0131983{col 71}{space 3}  .102419
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5298665{col 30}{space 2} .0290205{col 41}{space 1}   18.26{col 50}{space 3}0.000{col 58}{space 4} .4728417{col 71}{space 3} .5868912
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F(  4,   475) ={res}    7.44
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0156
                                                       {txt}Root MSE      = {res} .24346

{txt}{ralign 78:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~c{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_c {c |}{col 14}{res}{space 2}-.0104279{col 26}{space 2} .0228854{col 37}{space 1}   -0.46{col 46}{space 3}0.649{col 54}{space 4}-.0553971{col 67}{space 3} .0345414
{txt}{space 6}educ_z {c |}{col 14}{res}{space 2} .1054537{col 26}{space 2}   .02461{col 37}{space 1}    4.28{col 46}{space 3}0.000{col 54}{space 4} .0570957{col 67}{space 3} .1538117
{txt}educ_treat_c {c |}{col 14}{res}{space 2}-.0111721{col 26}{space 2} .0389395{col 37}{space 1}   -0.29{col 46}{space 3}0.774{col 54}{space 4}-.0876871{col 67}{space 3} .0653429
{txt}{space 3}educ_miss {c |}{col 14}{res}{space 2} .1516308{col 26}{space 2}  .091872{col 37}{space 1}    1.65{col 46}{space 3}0.100{col 54}{space 4}-.0288951{col 67}{space 3} .3321566
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}  .609514{col 26}{space 2} .0143288{col 37}{space 1}   42.54{col 46}{space 3}0.000{col 54}{space 4} .5813582{col 67}{space 3} .6376697
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: educ_z omitted because of collinearity

Linear regression                                      Number of obs ={res}    5244
                                                       {txt}F( 16,   475) ={res}    3.76
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0311
                                                       {txt}Root MSE      = {res} .24181

{txt}{ralign 82:(Std. Err. adjusted for {res:476} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_c{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_c {c |}{col 18}{res}{space 2}-.0126725{col 30}{space 2} .0224218{col 41}{space 1}   -0.57{col 50}{space 3}0.572{col 58}{space 4}-.0567307{col 71}{space 3} .0313856
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0473248{col 30}{space 2} .0292169{col 41}{space 1}    1.62{col 50}{space 3}0.106{col 58}{space 4}-.0100856{col 71}{space 3} .1047352
{txt}{space 4}educ_treat_c {c |}{col 18}{res}{space 2}-.0134687{col 30}{space 2} .0381268{col 41}{space 1}   -0.35{col 50}{space 3}0.724{col 58}{space 4}-.0883867{col 71}{space 3} .0614492
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0315661{col 30}{space 2} .0184611{col 41}{space 1}    1.71{col 50}{space 3}0.088{col 58}{space 4}-.0047094{col 71}{space 3} .0678417
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0247713{col 30}{space 2} .0128211{col 41}{space 1}   -1.93{col 50}{space 3}0.054{col 58}{space 4}-.0499644{col 71}{space 3} .0004218
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0414119{col 30}{space 2} .0298364{col 41}{space 1}    1.39{col 50}{space 3}0.166{col 58}{space 4}-.0172157{col 71}{space 3} .1000394
{txt}{space 10}read_z {c |}{col 18}{res}{space 2} .0059523{col 30}{space 2} .0162293{col 41}{space 1}    0.37{col 50}{space 3}0.714{col 58}{space 4}-.0259379{col 71}{space 3} .0378425
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0558541{col 30}{space 2} .0189442{col 41}{space 1}    2.95{col 50}{space 3}0.003{col 58}{space 4} .0186293{col 71}{space 3} .0930789
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .0859536{col 30}{space 2} .0598307{col 41}{space 1}    1.44{col 50}{space 3}0.151{col 58}{space 4} -.031612{col 71}{space 3} .2035192
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2} .0144046{col 30}{space 2} .0528585{col 41}{space 1}    0.27{col 50}{space 3}0.785{col 58}{space 4}-.0894607{col 71}{space 3}   .11827
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}-.0002631{col 30}{space 2} .0890407{col 41}{space 1}   -0.00{col 50}{space 3}0.998{col 58}{space 4}-.1752255{col 71}{space 3} .1746992
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .2237987{col 30}{space 2} .0754605{col 41}{space 1}    2.97{col 50}{space 3}0.003{col 58}{space 4}  .075521{col 71}{space 3} .3720764
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0015729{col 30}{space 2} .0462288{col 41}{space 1}   -0.03{col 50}{space 3}0.973{col 58}{space 4}-.0924112{col 71}{space 3} .0892654
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0924314{col 30}{space 2} .0234857{col 41}{space 1}    3.94{col 50}{space 3}0.000{col 58}{space 4} .0462828{col 71}{space 3} .1385801
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2} .1397909{col 30}{space 2} .1012275{col 41}{space 1}    1.38{col 50}{space 3}0.168{col 58}{space 4}-.0591182{col 71}{space 3} .3387001
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0471094{col 30}{space 2} .0238877{col 41}{space 1}    1.97{col 50}{space 3}0.049{col 58}{space 4} .0001708{col 71}{space 3}  .094048
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5348878{col 30}{space 2} .0305113{col 41}{space 1}   17.53{col 50}{space 3}0.000{col 58}{space 4} .4749341{col 71}{space 3} .5948416
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F(  4,   483) ={res}    7.72
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0175
                                                       {txt}Root MSE      = {res} .25169

{txt}{ralign 78:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~d{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_d {c |}{col 14}{res}{space 2}-.0214685{col 26}{space 2} .0240965{col 37}{space 1}   -0.89{col 46}{space 3}0.373{col 54}{space 4}-.0688154{col 67}{space 3} .0258784
{txt}{space 6}educ_z {c |}{col 14}{res}{space 2} .1055891{col 26}{space 2} .0246089{col 37}{space 1}    4.29{col 46}{space 3}0.000{col 54}{space 4} .0572353{col 67}{space 3} .1539429
{txt}educ_treat_d {c |}{col 14}{res}{space 2}-.0000524{col 26}{space 2} .0420374{col 37}{space 1}   -0.00{col 46}{space 3}0.999{col 54}{space 4}-.0826512{col 67}{space 3} .0825464
{txt}{space 3}educ_miss {c |}{col 14}{res}{space 2} .1790547{col 26}{space 2} .0901795{col 37}{space 1}    1.99{col 46}{space 3}0.048{col 54}{space 4} .0018621{col 67}{space 3} .3562474
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6094361{col 26}{space 2}  .014327{col 37}{space 1}   42.54{col 46}{space 3}0.000{col 54}{space 4} .5812852{col 67}{space 3} .6375871
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: educ_z omitted because of collinearity

Linear regression                                      Number of obs ={res}    5207
                                                       {txt}F( 16,   483) ={res}    4.96
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0437
                                                       {txt}Root MSE      = {res} .24861

{txt}{ralign 82:(Std. Err. adjusted for {res:484} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_d{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_d {c |}{col 18}{res}{space 2} -.023925{col 30}{space 2} .0234335{col 41}{space 1}   -1.02{col 50}{space 3}0.308{col 58}{space 4}-.0699691{col 71}{space 3} .0221192
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2} .0517633{col 30}{space 2} .0296405{col 41}{space 1}    1.75{col 50}{space 3}0.081{col 58}{space 4}-.0064771{col 71}{space 3} .1100036
{txt}{space 4}educ_treat_d {c |}{col 18}{res}{space 2} .0013256{col 30}{space 2} .0410071{col 41}{space 1}    0.03{col 50}{space 3}0.974{col 58}{space 4}-.0792488{col 71}{space 3} .0819001
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0232307{col 30}{space 2}  .019194{col 41}{space 1}    1.21{col 50}{space 3}0.227{col 58}{space 4}-.0144832{col 71}{space 3} .0609447
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0036372{col 30}{space 2} .0144672{col 41}{space 1}   -0.25{col 50}{space 3}0.802{col 58}{space 4}-.0320637{col 71}{space 3} .0247892
{txt}{space 11}age_z {c |}{col 18}{res}{space 2} .0295736{col 30}{space 2} .0324802{col 41}{space 1}    0.91{col 50}{space 3}0.363{col 58}{space 4}-.0342465{col 71}{space 3} .0933936
{txt}{space 10}read_z {c |}{col 18}{res}{space 2}-.0110053{col 30}{space 2} .0166474{col 41}{space 1}   -0.66{col 50}{space 3}0.509{col 58}{space 4}-.0437156{col 71}{space 3} .0217051
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0785621{col 30}{space 2} .0201456{col 41}{space 1}    3.90{col 50}{space 3}0.000{col 58}{space 4} .0389783{col 71}{space 3} .1181459
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .2304958{col 30}{space 2} .0587309{col 41}{space 1}    3.92{col 50}{space 3}0.000{col 58}{space 4} .1150961{col 71}{space 3} .3458955
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0572759{col 30}{space 2} .0512378{col 41}{space 1}   -1.12{col 50}{space 3}0.264{col 58}{space 4}-.1579525{col 71}{space 3} .0434006
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2}-.0704609{col 30}{space 2} .0838744{col 41}{space 1}   -0.84{col 50}{space 3}0.401{col 58}{space 4}-.2352646{col 71}{space 3} .0943428
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .1061786{col 30}{space 2} .0868155{col 41}{space 1}    1.22{col 50}{space 3}0.222{col 58}{space 4}-.0644041{col 71}{space 3} .2767613
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0852179{col 30}{space 2} .0566297{col 41}{space 1}   -1.50{col 50}{space 3}0.133{col 58}{space 4} -.196489{col 71}{space 3} .0260531
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .1077839{col 30}{space 2} .0256032{col 41}{space 1}    4.21{col 50}{space 3}0.000{col 58}{space 4} .0574764{col 71}{space 3} .1580913
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2} .1534308{col 30}{space 2} .0829768{col 41}{space 1}    1.85{col 50}{space 3}0.065{col 58}{space 4}-.0096093{col 71}{space 3} .3164708
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0752191{col 30}{space 2} .0254068{col 41}{space 1}    2.96{col 50}{space 3}0.003{col 58}{space 4} .0252977{col 71}{space 3} .1251406
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5340687{col 30}{space 2} .0307822{col 41}{space 1}   17.35{col 50}{space 3}0.000{col 58}{space 4} .4735851{col 71}{space 3} .5945523
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F(  4,   490) ={res}   10.33
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0224
                                                       {txt}Root MSE      = {res} .23411

{txt}{ralign 78:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}policy_pre~e{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      t{col 46}   P>|t|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 5}treat_e {c |}{col 14}{res}{space 2} .0146901{col 26}{space 2} .0214309{col 37}{space 1}    0.69{col 46}{space 3}0.493{col 54}{space 4}-.0274178{col 67}{space 3} .0567979
{txt}{space 6}educ_z {c |}{col 14}{res}{space 2} .1036682{col 26}{space 2} .0246303{col 37}{space 1}    4.21{col 46}{space 3}0.000{col 54}{space 4} .0552742{col 67}{space 3} .1520622
{txt}educ_treat_e {c |}{col 14}{res}{space 2}-.0037681{col 26}{space 2} .0387242{col 37}{space 1}   -0.10{col 46}{space 3}0.923{col 54}{space 4}-.0798541{col 67}{space 3} .0723179
{txt}{space 3}educ_miss {c |}{col 14}{res}{space 2}-.2100285{col 26}{space 2} .0666636{col 37}{space 1}   -3.15{col 46}{space 3}0.002{col 54}{space 4}-.3410104{col 67}{space 3}-.0790466
{txt}{space 7}_cons {c |}{col 14}{res}{space 2} .6105404{col 26}{space 2} .0143566{col 37}{space 1}   42.53{col 46}{space 3}0.000{col 54}{space 4} .5823323{col 67}{space 3} .6387484
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: educ_z omitted because of collinearity

Linear regression                                      Number of obs ={res}    5376
                                                       {txt}F( 16,   490) ={res}    4.69
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0451
                                                       {txt}Root MSE      = {res} .23163

{txt}{ralign 82:(Std. Err. adjusted for {res:491} clusters in psu_new)}
{hline 17}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 18}{c |}{col 30}    Robust
{col 1}   policy_pref_e{col 18}{c |}      Coef.{col 30}   Std. Err.{col 42}      t{col 50}   P>|t|{col 58}     [95% Con{col 71}f. Interval]
{hline 17}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 9}treat_e {c |}{col 18}{res}{space 2} .0139195{col 30}{space 2} .0207126{col 41}{space 1}    0.67{col 50}{space 3}0.502{col 58}{space 4}-.0267769{col 71}{space 3} .0546159
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2}  .038789{col 30}{space 2} .0288932{col 41}{space 1}    1.34{col 50}{space 3}0.180{col 58}{space 4}-.0179809{col 71}{space 3}  .095559
{txt}{space 4}educ_treat_e {c |}{col 18}{res}{space 2}-.0119867{col 30}{space 2} .0371172{col 41}{space 1}   -0.32{col 50}{space 3}0.747{col 58}{space 4}-.0849152{col 71}{space 3} .0609417
{txt}{space 8}gender_z {c |}{col 18}{res}{space 2} .0398203{col 30}{space 2} .0173717{col 41}{space 1}    2.29{col 50}{space 3}0.022{col 58}{space 4} .0056881{col 71}{space 3} .0739526
{txt}{space 9}headh_z {c |}{col 18}{res}{space 2}-.0074271{col 30}{space 2}  .012388{col 41}{space 1}   -0.60{col 50}{space 3}0.549{col 58}{space 4}-.0317672{col 71}{space 3}  .016913
{txt}{space 11}age_z {c |}{col 18}{res}{space 2}  .003345{col 30}{space 2}  .030314{col 41}{space 1}    0.11{col 50}{space 3}0.912{col 58}{space 4}-.0562165{col 71}{space 3} .0629066
{txt}{space 10}read_z {c |}{col 18}{res}{space 2}-.0023602{col 30}{space 2} .0154651{col 41}{space 1}   -0.15{col 50}{space 3}0.879{col 58}{space 4}-.0327463{col 71}{space 3} .0280258
{txt}{space 10}math_z {c |}{col 18}{res}{space 2} .0760751{col 30}{space 2} .0173352{col 41}{space 1}    4.39{col 50}{space 3}0.000{col 58}{space 4} .0420146{col 71}{space 3} .1101356
{txt}{space 10}educ_z {c |}{col 18}{res}{space 2}        0{col 30}{txt}  (omitted)
{space 3}houseexpend_z {c |}{col 18}{res}{space 2} .0922761{col 30}{space 2} .0520801{col 41}{space 1}    1.77{col 50}{space 3}0.077{col 58}{space 4}-.0100517{col 71}{space 3} .1946038
{txt}{space 4}assetindex_z {c |}{col 18}{res}{space 2}-.0164482{col 30}{space 2} .0473748{col 41}{space 1}   -0.35{col 50}{space 3}0.729{col 58}{space 4} -.109531{col 71}{space 3} .0766346
{txt}{space 6}headh_miss {c |}{col 18}{res}{space 2} .0630699{col 30}{space 2} .0513148{col 41}{space 1}    1.23{col 50}{space 3}0.220{col 58}{space 4}-.0377542{col 71}{space 3} .1638941
{txt}{space 8}age_miss {c |}{col 18}{res}{space 2} .0034327{col 30}{space 2} .0699827{col 41}{space 1}    0.05{col 50}{space 3}0.961{col 58}{space 4}-.1340705{col 71}{space 3} .1409359
{txt}{space 7}read_miss {c |}{col 18}{res}{space 2}-.0133801{col 30}{space 2} .0488759{col 41}{space 1}   -0.27{col 50}{space 3}0.784{col 58}{space 4}-.1094123{col 71}{space 3} .0826522
{txt}{space 7}math_miss {c |}{col 18}{res}{space 2} .0833967{col 30}{space 2} .0247288{col 41}{space 1}    3.37{col 50}{space 3}0.001{col 58}{space 4} .0348091{col 71}{space 3} .1319844
{txt}{space 7}educ_miss {c |}{col 18}{res}{space 2}-.2004282{col 30}{space 2} .0603761{col 41}{space 1}   -3.32{col 50}{space 3}0.001{col 58}{space 4}-.3190563{col 71}{space 3}-.0818001
{txt}houseexpend_miss {c |}{col 18}{res}{space 2} .0504425{col 30}{space 2} .0231374{col 41}{space 1}    2.18{col 50}{space 3}0.030{col 58}{space 4} .0049817{col 71}{space 3} .0959033
{txt}{space 11}_cons {c |}{col 18}{res}{space 2} .5399497{col 30}{space 2} .0279197{col 41}{space 1}   19.34{col 50}{space 3}0.000{col 58}{space 4} .4850927{col 71}{space 3} .5948068
{txt}{hline 17}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         
. /// APPENDIX TABLE 3: Effects of Observed Poverty on Support for Militant Groups  
> 
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' lowexp20_urprov highexp20_urprov treat_`x' lowexp20_urprov_`x' highexp20_urprov_`x', cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' lowexp20_urprov highexp20_urprov treat_`x' lowexp20_urprov_`x' highexp20_urprov_`x' gender_z headh_z age_z read_z math_z educ_z assetindex_z headh_miss age_miss read_miss math_miss educ_miss, cluster(psu_new)
{txt}  4{com}.                 areg policy_pref_`x' lowexp20_urprov highexp20_urprov treat_`x' lowexp20_urprov_`x' highexp20_urprov_`x', cluster(a7) a(treatprov)
{txt}  5{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  5,   952) ={res}    6.77
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0106
                                                       {txt}Root MSE      = {res} .25381

{txt}{ralign 92:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}     policy_pref_militancy{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      t{col 60}   P>|t|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}lowexp20_urprov {c |}{col 28}{res}{space 2}-.0136784{col 40}{space 2} .0160782{col 51}{space 1}   -0.85{col 60}{space 3}0.395{col 68}{space 4}-.0452313{col 81}{space 3} .0178744
{txt}{space 10}highexp20_urprov {c |}{col 28}{res}{space 2} .0084175{col 40}{space 2} .0162252{col 51}{space 1}    0.52{col 60}{space 3}0.604{col 68}{space 4}-.0234238{col 81}{space 3} .0402588
{txt}{space 11}treat_militancy {c |}{col 28}{res}{space 2}-.0106003{col 40}{space 2} .0165208{col 51}{space 1}   -0.64{col 60}{space 3}0.521{col 68}{space 4}-.0430218{col 81}{space 3} .0218212
{txt}{space 1}lowexp20_urprov_militancy {c |}{col 28}{res}{space 2}-.0318086{col 40}{space 2} .0204949{col 51}{space 1}   -1.55{col 60}{space 3}0.121{col 68}{space 4} -.072029{col 81}{space 3} .0084118
{txt}highexp20_urprov_militancy {c |}{col 28}{res}{space 2} .0341845{col 40}{space 2} .0194241{col 51}{space 1}    1.76{col 60}{space 3}0.079{col 68}{space 4}-.0039346{col 81}{space 3} .0723036
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .6391102{col 40}{space 2} .0138908{col 51}{space 1}   46.01{col 60}{space 3}0.000{col 68}{space 4} .6118501{col 81}{space 3} .6663703
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 17,   952) ={res}    6.89
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0324
                                                       {txt}Root MSE      = {res} .25114

{txt}{ralign 92:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}     policy_pref_militancy{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      t{col 60}   P>|t|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}lowexp20_urprov {c |}{col 28}{res}{space 2}-.0060181{col 40}{space 2} .0154834{col 51}{space 1}   -0.39{col 60}{space 3}0.698{col 68}{space 4}-.0364036{col 81}{space 3} .0243674
{txt}{space 10}highexp20_urprov {c |}{col 28}{res}{space 2} .0021656{col 40}{space 2} .0157346{col 51}{space 1}    0.14{col 60}{space 3}0.891{col 68}{space 4}-.0287129{col 81}{space 3} .0330441
{txt}{space 11}treat_militancy {c |}{col 28}{res}{space 2}-.0153303{col 40}{space 2} .0161745{col 51}{space 1}   -0.95{col 60}{space 3}0.343{col 68}{space 4}-.0470721{col 81}{space 3} .0164115
{txt}{space 1}lowexp20_urprov_militancy {c |}{col 28}{res}{space 2}-.0314522{col 40}{space 2} .0195889{col 51}{space 1}   -1.61{col 60}{space 3}0.109{col 68}{space 4}-.0698946{col 81}{space 3} .0069903
{txt}highexp20_urprov_militancy {c |}{col 28}{res}{space 2} .0306214{col 40}{space 2} .0188401{col 51}{space 1}    1.63{col 60}{space 3}0.104{col 68}{space 4}-.0063514{col 81}{space 3} .0675943
{txt}{space 18}gender_z {c |}{col 28}{res}{space 2} .0257631{col 40}{space 2} .0137052{col 51}{space 1}    1.88{col 60}{space 3}0.060{col 68}{space 4}-.0011328{col 81}{space 3} .0526591
{txt}{space 19}headh_z {c |}{col 28}{res}{space 2}-.0050626{col 40}{space 2} .0095141{col 51}{space 1}   -0.53{col 60}{space 3}0.595{col 68}{space 4}-.0237335{col 81}{space 3} .0136084
{txt}{space 21}age_z {c |}{col 28}{res}{space 2} .0349087{col 40}{space 2}  .021627{col 51}{space 1}    1.61{col 60}{space 3}0.107{col 68}{space 4}-.0075335{col 81}{space 3} .0773508
{txt}{space 20}read_z {c |}{col 28}{res}{space 2}-.0206144{col 40}{space 2} .0121574{col 51}{space 1}   -1.70{col 60}{space 3}0.090{col 68}{space 4}-.0444728{col 81}{space 3} .0032439
{txt}{space 20}math_z {c |}{col 28}{res}{space 2} .0637644{col 40}{space 2}  .014033{col 51}{space 1}    4.54{col 60}{space 3}0.000{col 68}{space 4} .0362252{col 81}{space 3} .0913037
{txt}{space 20}educ_z {c |}{col 28}{res}{space 2} .0655794{col 40}{space 2} .0198335{col 51}{space 1}    3.31{col 60}{space 3}0.001{col 68}{space 4} .0266571{col 81}{space 3} .1045018
{txt}{space 14}assetindex_z {c |}{col 28}{res}{space 2}-.0353228{col 40}{space 2} .0357664{col 51}{space 1}   -0.99{col 60}{space 3}0.324{col 68}{space 4}-.1055128{col 81}{space 3} .0348672
{txt}{space 16}headh_miss {c |}{col 28}{res}{space 2}-.0434922{col 40}{space 2} .0498479{col 51}{space 1}   -0.87{col 60}{space 3}0.383{col 68}{space 4}-.1413166{col 81}{space 3} .0543322
{txt}{space 18}age_miss {c |}{col 28}{res}{space 2} .1935559{col 40}{space 2} .0534517{col 51}{space 1}    3.62{col 60}{space 3}0.000{col 68}{space 4}  .088659{col 81}{space 3} .2984527
{txt}{space 17}read_miss {c |}{col 28}{res}{space 2}-.0801338{col 40}{space 2} .0392183{col 51}{space 1}   -2.04{col 60}{space 3}0.041{col 68}{space 4}-.1570982{col 81}{space 3}-.0031695
{txt}{space 17}math_miss {c |}{col 28}{res}{space 2} .0887341{col 40}{space 2} .0172674{col 51}{space 1}    5.14{col 60}{space 3}0.000{col 68}{space 4} .0548476{col 81}{space 3} .1226205
{txt}{space 17}educ_miss {c |}{col 28}{res}{space 2} .1337463{col 40}{space 2} .0583012{col 51}{space 1}    2.29{col 60}{space 3}0.022{col 68}{space 4} .0193326{col 81}{space 3}   .24816
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .5782485{col 40}{space 2} .0244421{col 51}{space 1}   23.66{col 60}{space 3}0.000{col 68}{space 4} .5302819{col 81}{space 3} .6262151
{txt}{hline 27}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: treat_militancy omitted because of collinearity
{res}
{txt}Linear regression, absorbing indicators{col 51}Number of obs{col 67}= {res}     10502
{txt}{col 51}F({res}   4{txt},{res}     66{txt}){col 67}= {res}      4.31
{txt}{col 51}Prob > F{col 67}= {res}    0.0037
{txt}{col 51}R-squared{col 67}= {res}    0.1422
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1411
{txt}{col 51}Root MSE{col 67}= {res}    0.2365

{txt}{ralign 92:(Std. Err. adjusted for {res:67} clusters in a7)}
{hline 27}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 28}{c |}{col 40}    Robust
{col 1}     policy_pref_militancy{col 28}{c |}      Coef.{col 40}   Std. Err.{col 52}      t{col 60}   P>|t|{col 68}     [95% Con{col 81}f. Interval]
{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 11}lowexp20_urprov {c |}{col 28}{res}{space 2}   -.0293{col 40}{space 2} .0179121{col 51}{space 1}   -1.64{col 60}{space 3}0.107{col 68}{space 4}-.0650627{col 81}{space 3} .0064627
{txt}{space 10}highexp20_urprov {c |}{col 28}{res}{space 2} .0111668{col 40}{space 2} .0190752{col 51}{space 1}    0.59{col 60}{space 3}0.560{col 68}{space 4} -.026918{col 81}{space 3} .0492516
{txt}{space 11}treat_militancy {c |}{col 28}{res}{space 2}        0{col 40}{txt}  (omitted)
{space 1}lowexp20_urprov_militancy {c |}{col 28}{res}{space 2}-.0135891{col 40}{space 2} .0197133{col 51}{space 1}   -0.69{col 60}{space 3}0.493{col 68}{space 4}-.0529479{col 81}{space 3} .0257697
{txt}highexp20_urprov_militancy {c |}{col 28}{res}{space 2}  .022528{col 40}{space 2} .0182115{col 51}{space 1}    1.24{col 60}{space 3}0.220{col 68}{space 4}-.0138325{col 81}{space 3} .0588884
{txt}{space 21}_cons {c |}{col 28}{res}{space 2} .6328711{col 40}{space 2} .0128959{col 51}{space 1}   49.08{col 60}{space 3}0.000{col 68}{space 4} .6071235{col 81}{space 3} .6586186
{txt}{hline 27}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
                 treatprov {c |}   absorbed                                      (10 categories)

{com}. 
. 
. /// APPENDIX TABLE 4: Effects of Experimental Treatments on Support for Militant Groups  
> 
. // Columns 1-3  
. 
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x', level(90) cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' *_z *_miss, level(90) cluster(psu_new)
{txt}  4{com}.                 areg policy_pref_`x' treat_`x' poverty poverty_treat_`x', level(90) cluster(a7) a(treatprov)
{txt}  5{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  3,   952) ={res}    1.32
                                                       {txt}Prob > F      = {res} 0.2678
                                                       {txt}R-squared     = {res} 0.0025
                                                       {txt}Root MSE      = {res} .25482

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [90% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0151704{col 37}{space 2} .0200743{col 48}{space 1}    0.76{col 57}{space 3}0.450{col 65}{space 4}-.0178811{col 78}{space 3} .0482218
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0312276{col 37}{space 2}  .023629{col 48}{space 1}    1.32{col 57}{space 3}0.187{col 65}{space 4}-.0076766{col 78}{space 3} .0701318
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0523725{col 37}{space 2} .0286912{col 48}{space 1}   -1.83{col 57}{space 3}0.068{col 65}{space 4}-.0996113{col 78}{space 3}-.0051338
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .6226903{col 37}{space 2} .0167844{col 48}{space 1}   37.10{col 57}{space 3}0.000{col 65}{space 4} .5950555{col 78}{space 3} .6503252
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 17,   952) ={res}    7.82
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0369
                                                       {txt}Root MSE      = {res} .25056

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [90% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0064297{col 37}{space 2} .0196452{col 48}{space 1}    0.33{col 57}{space 3}0.744{col 65}{space 4}-.0259153{col 78}{space 3} .0387747
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0223075{col 37}{space 2} .0228437{col 48}{space 1}    0.98{col 57}{space 3}0.329{col 65}{space 4}-.0153036{col 78}{space 3} .0599186
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0461845{col 37}{space 2} .0276694{col 48}{space 1}   -1.67{col 57}{space 3}0.095{col 65}{space 4} -.091741{col 78}{space 3}-.0006281
{txt}{space 15}gender_z {c |}{col 25}{res}{space 2} .0263965{col 37}{space 2} .0136055{col 48}{space 1}    1.94{col 57}{space 3}0.053{col 65}{space 4} .0039957{col 78}{space 3} .0487973
{txt}{space 16}headh_z {c |}{col 25}{res}{space 2}-.0044241{col 37}{space 2} .0094328{col 48}{space 1}   -0.47{col 57}{space 3}0.639{col 65}{space 4}-.0199548{col 78}{space 3} .0111065
{txt}{space 18}age_z {c |}{col 25}{res}{space 2} .0274621{col 37}{space 2} .0214527{col 48}{space 1}    1.28{col 57}{space 3}0.201{col 65}{space 4}-.0078588{col 78}{space 3} .0627829
{txt}{space 17}read_z {c |}{col 25}{res}{space 2}-.0201941{col 37}{space 2} .0122219{col 48}{space 1}   -1.65{col 57}{space 3}0.099{col 65}{space 4}-.0403168{col 78}{space 3}-.0000713
{txt}{space 17}math_z {c |}{col 25}{res}{space 2} .0647909{col 37}{space 2}  .013921{col 48}{space 1}    4.65{col 57}{space 3}0.000{col 65}{space 4} .0418706{col 78}{space 3} .0877113
{txt}{space 17}educ_z {c |}{col 25}{res}{space 2} .0534455{col 37}{space 2} .0198419{col 48}{space 1}    2.69{col 57}{space 3}0.007{col 65}{space 4} .0207767{col 78}{space 3} .0861144
{txt}{space 10}houseexpend_z {c |}{col 25}{res}{space 2} .2336135{col 37}{space 2} .0416998{col 48}{space 1}    5.60{col 57}{space 3}0.000{col 65}{space 4} .1649565{col 78}{space 3} .3022704
{txt}{space 11}assetindex_z {c |}{col 25}{res}{space 2}-.0459897{col 37}{space 2} .0366276{col 48}{space 1}   -1.26{col 57}{space 3}0.210{col 65}{space 4}-.1062954{col 78}{space 3} .0143161
{txt}{space 13}headh_miss {c |}{col 25}{res}{space 2}-.0349633{col 37}{space 2} .0495517{col 48}{space 1}   -0.71{col 57}{space 3}0.481{col 65}{space 4} -.116548{col 78}{space 3} .0466215
{txt}{space 15}age_miss {c |}{col 25}{res}{space 2} .1800489{col 37}{space 2} .0519805{col 48}{space 1}    3.46{col 57}{space 3}0.001{col 65}{space 4} .0944653{col 78}{space 3} .2656326
{txt}{space 14}read_miss {c |}{col 25}{res}{space 2}-.0836812{col 37}{space 2} .0400269{col 48}{space 1}   -2.09{col 57}{space 3}0.037{col 65}{space 4}-.1495837{col 78}{space 3}-.0177788
{txt}{space 14}math_miss {c |}{col 25}{res}{space 2} .0866098{col 37}{space 2} .0170953{col 48}{space 1}    5.07{col 57}{space 3}0.000{col 65}{space 4} .0584632{col 78}{space 3} .1147565
{txt}{space 14}educ_miss {c |}{col 25}{res}{space 2} .1237602{col 37}{space 2} .0566247{col 48}{space 1}    2.19{col 57}{space 3}0.029{col 65}{space 4} .0305302{col 78}{space 3} .2169902
{txt}{space 7}houseexpend_miss {c |}{col 25}{res}{space 2} .0768795{col 37}{space 2} .0184574{col 48}{space 1}    4.17{col 57}{space 3}0.000{col 65}{space 4} .0464902{col 78}{space 3} .1072689
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}  .531778{col 37}{space 2}  .025329{col 48}{space 1}   20.99{col 57}{space 3}0.000{col 65}{space 4} .4900749{col 78}{space 3} .5734811
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: treat_militancy omitted because of collinearity
{res}
{txt}Linear regression, absorbing indicators{col 51}Number of obs{col 67}= {res}     10492
{txt}{col 51}F({res}   2{txt},{res}     66{txt}){col 67}= {res}      1.44
{txt}{col 51}Prob > F{col 67}= {res}    0.2452
{txt}{col 51}R-squared{col 67}= {res}    0.1350
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1341
{txt}{col 51}Root MSE{col 67}= {res}    0.2374

{txt}{ralign 89:(Std. Err. adjusted for {res:67} clusters in a7)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [90% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2}        0{col 37}{txt}  (omitted)
{space 16}poverty {c |}{col 25}{res}{space 2} .0241052{col 37}{space 2} .0182452{col 48}{space 1}    1.32{col 57}{space 3}0.191{col 65}{space 4}-.0063328{col 78}{space 3} .0545431
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0357045{col 37}{space 2} .0210942{col 48}{space 1}   -1.69{col 57}{space 3}0.095{col 65}{space 4}-.0708954{col 78}{space 3}-.0005136
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .6313793{col 37}{space 2} .0130167{col 48}{space 1}   48.51{col 57}{space 3}0.000{col 65}{space 4}  .609664{col 78}{space 3} .6530947
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              treatprov {c |}   absorbed                                      (10 categories)

{com}. 
. // Columns 4-6  
. 
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' natviol natviol_treat_`x', level(90) cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' natviol natviol_treat_`x' *_z *_miss, level(90) cluster(psu_new)  
{txt}  4{com}.                 areg policy_pref_`x' treat_`x' natviol natviol_treat_`x', level(90) cluster(a7) a(treatprov)    
{txt}  5{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    5300
                                                       {txt}F(  3,   486) ={res}    4.23
                                                       {txt}Prob > F      = {res} 0.0058
                                                       {txt}R-squared     = {res} 0.0108
                                                       {txt}Root MSE      = {res} .25694

{txt}{ralign 89:(Std. Err. adjusted for {res:487} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [90% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0251245{col 37}{space 2} .0296855{col 48}{space 1}    0.85{col 57}{space 3}0.398{col 65}{space 4}-.0237971{col 78}{space 3} .0740461
{txt}{space 16}natviol {c |}{col 25}{res}{space 2} .0863599{col 37}{space 2} .0316784{col 48}{space 1}    2.73{col 57}{space 3}0.007{col 65}{space 4}  .034154{col 78}{space 3} .1385658
{txt}natviol_treat_militancy {c |}{col 25}{res}{space 2}-.1073786{col 37}{space 2} .0393457{col 48}{space 1}   -2.73{col 57}{space 3}0.007{col 65}{space 4}-.1722201{col 78}{space 3}-.0425371
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5973303{col 37}{space 2} .0255819{col 48}{space 1}   23.35{col 57}{space 3}0.000{col 65}{space 4} .5551714{col 78}{space 3} .6394892
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5300
                                                       {txt}F( 17,   486) ={res}    5.75
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0484
                                                       {txt}Root MSE      = {res} .25234

{txt}{ralign 89:(Std. Err. adjusted for {res:487} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [90% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0237234{col 37}{space 2} .0286552{col 48}{space 1}    0.83{col 57}{space 3}0.408{col 65}{space 4}-.0235001{col 78}{space 3}  .070947
{txt}{space 16}natviol {c |}{col 25}{res}{space 2} .0911895{col 37}{space 2}  .030875{col 48}{space 1}    2.95{col 57}{space 3}0.003{col 65}{space 4} .0403076{col 78}{space 3} .1420714
{txt}natviol_treat_militancy {c |}{col 25}{res}{space 2}-.1124792{col 37}{space 2} .0382936{col 48}{space 1}   -2.94{col 57}{space 3}0.003{col 65}{space 4}-.1755869{col 78}{space 3}-.0493715
{txt}{space 15}gender_z {c |}{col 25}{res}{space 2} .0227427{col 37}{space 2} .0196667{col 48}{space 1}    1.16{col 57}{space 3}0.248{col 65}{space 4}-.0096679{col 78}{space 3} .0551533
{txt}{space 16}headh_z {c |}{col 25}{res}{space 2} .0009867{col 37}{space 2}  .013188{col 48}{space 1}    0.07{col 57}{space 3}0.940{col 65}{space 4}-.0207471{col 78}{space 3} .0227205
{txt}{space 18}age_z {c |}{col 25}{res}{space 2} .0190562{col 37}{space 2} .0300908{col 48}{space 1}    0.63{col 57}{space 3}0.527{col 65}{space 4}-.0305333{col 78}{space 3} .0686457
{txt}{space 17}read_z {c |}{col 25}{res}{space 2}-.0300252{col 37}{space 2} .0171155{col 48}{space 1}   -1.75{col 57}{space 3}0.080{col 65}{space 4}-.0582314{col 78}{space 3} -.001819
{txt}{space 17}math_z {c |}{col 25}{res}{space 2} .0820331{col 37}{space 2}  .018948{col 48}{space 1}    4.33{col 57}{space 3}0.000{col 65}{space 4} .0508069{col 78}{space 3} .1132593
{txt}{space 17}educ_z {c |}{col 25}{res}{space 2} .0384389{col 37}{space 2} .0281497{col 48}{space 1}    1.37{col 57}{space 3}0.173{col 65}{space 4}-.0079517{col 78}{space 3} .0848295
{txt}{space 10}houseexpend_z {c |}{col 25}{res}{space 2} .2120047{col 37}{space 2} .0575642{col 48}{space 1}    3.68{col 57}{space 3}0.000{col 65}{space 4} .1171392{col 78}{space 3} .3068702
{txt}{space 11}assetindex_z {c |}{col 25}{res}{space 2}-.0112702{col 37}{space 2} .0483286{col 48}{space 1}   -0.23{col 57}{space 3}0.816{col 65}{space 4}-.0909155{col 78}{space 3} .0683752
{txt}{space 13}headh_miss {c |}{col 25}{res}{space 2}-.0705411{col 37}{space 2} .0560576{col 48}{space 1}   -1.26{col 57}{space 3}0.209{col 65}{space 4}-.1629237{col 78}{space 3} .0218415
{txt}{space 15}age_miss {c |}{col 25}{res}{space 2} .1318017{col 37}{space 2} .0608341{col 48}{space 1}    2.17{col 57}{space 3}0.031{col 65}{space 4} .0315474{col 78}{space 3} .2320561
{txt}{space 14}read_miss {c |}{col 25}{res}{space 2}-.0839447{col 37}{space 2} .0416637{col 48}{space 1}   -2.01{col 57}{space 3}0.044{col 65}{space 4}-.1526063{col 78}{space 3}-.0152831
{txt}{space 14}math_miss {c |}{col 25}{res}{space 2} .0911091{col 37}{space 2} .0230412{col 48}{space 1}    3.95{col 57}{space 3}0.000{col 65}{space 4} .0531373{col 78}{space 3} .1290808
{txt}{space 14}educ_miss {c |}{col 25}{res}{space 2}  .177672{col 37}{space 2} .0698375{col 48}{space 1}    2.54{col 57}{space 3}0.011{col 65}{space 4} .0625802{col 78}{space 3} .2927638
{txt}{space 7}houseexpend_miss {c |}{col 25}{res}{space 2} .1040302{col 37}{space 2} .0268347{col 48}{space 1}    3.88{col 57}{space 3}0.000{col 65}{space 4} .0598068{col 78}{space 3} .1482536
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .4822612{col 37}{space 2} .0372275{col 48}{space 1}   12.95{col 57}{space 3}0.000{col 65}{space 4} .4209105{col 78}{space 3}  .543612
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: treat_militancy omitted because of collinearity
{res}
{txt}Linear regression, absorbing indicators{col 51}Number of obs{col 67}= {res}      5309
{txt}{col 51}F({res}   2{txt},{res}     66{txt}){col 67}= {res}      3.46
{txt}{col 51}Prob > F{col 67}= {res}    0.0374
{txt}{col 51}R-squared{col 67}= {res}    0.1352
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1334
{txt}{col 51}Root MSE{col 67}= {res}    0.2404

{txt}{ralign 89:(Std. Err. adjusted for {res:67} clusters in a7)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [90% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2}        0{col 37}{txt}  (omitted)
{space 16}natviol {c |}{col 25}{res}{space 2} .0623022{col 37}{space 2} .0254038{col 48}{space 1}    2.45{col 57}{space 3}0.017{col 65}{space 4} .0199218{col 78}{space 3} .1046825
{txt}natviol_treat_militancy {c |}{col 25}{res}{space 2}-.1043483{col 37}{space 2} .0414666{col 48}{space 1}   -2.52{col 57}{space 3}0.014{col 65}{space 4}-.1735258{col 78}{space 3}-.0351708
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .6268227{col 37}{space 2} .0157318{col 48}{space 1}   39.84{col 57}{space 3}0.000{col 65}{space 4} .6005778{col 78}{space 3} .6530676
{txt}{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
              treatprov {c |}   absorbed                                      (10 categories)

{com}. 
. // Columns 7-9 
. 
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' n01 n10 n11 n01_treat_`x' n10_treat_`x' n11_treat_`x', cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' n01 n10 n11 n01_treat_`x' n10_treat_`x' n11_treat_`x' *_z *_miss, cluster(psu_new)
{txt}  4{com}.                 areg policy_pref_`x' treat_`x' n01 n10 n11 n01_treat_`x' n10_treat_`x' n11_treat_`x', cluster(a7) a(treatprov)  
{txt}  5{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    5300
                                                       {txt}F(  7,   486) ={res}    1.98
                                                       {txt}Prob > F      = {res} 0.0562
                                                       {txt}R-squared     = {res} 0.0126
                                                       {txt}Root MSE      = {res} .25681

{txt}{ralign 85:(Std. Err. adjusted for {res:487} clusters in psu_new)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}policy_pref_milit~y{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}treat_militancy {c |}{col 21}{res}{space 2} .0340567{col 33}{space 2} .0418165{col 44}{space 1}    0.81{col 53}{space 3}0.416{col 61}{space 4}-.0481068{col 74}{space 3} .1162202
{txt}{space 16}n01 {c |}{col 21}{res}{space 2} .0784481{col 33}{space 2} .0456006{col 44}{space 1}    1.72{col 53}{space 3}0.086{col 61}{space 4}-.0111505{col 74}{space 3} .1680468
{txt}{space 16}n10 {c |}{col 21}{res}{space 2}  .016982{col 33}{space 2} .0500968{col 44}{space 1}    0.34{col 53}{space 3}0.735{col 61}{space 4} -.081451{col 74}{space 3}  .115415
{txt}{space 16}n11 {c |}{col 21}{res}{space 2} .1087445{col 33}{space 2} .0463658{col 44}{space 1}    2.35{col 53}{space 3}0.019{col 61}{space 4} .0176423{col 74}{space 3} .1998466
{txt}n01_treat_militancy {c |}{col 21}{res}{space 2}-.0866375{col 33}{space 2} .0549559{col 44}{space 1}   -1.58{col 53}{space 3}0.116{col 61}{space 4}-.1946179{col 74}{space 3} .0213429
{txt}n10_treat_militancy {c |}{col 21}{res}{space 2}-.0196071{col 33}{space 2} .0582728{col 44}{space 1}   -0.34{col 53}{space 3}0.737{col 61}{space 4}-.1341049{col 74}{space 3} .0948907
{txt}n11_treat_militancy {c |}{col 21}{res}{space 2}-.1458224{col 33}{space 2} .0558326{col 44}{space 1}   -2.61{col 53}{space 3}0.009{col 61}{space 4}-.2555255{col 74}{space 3}-.0361193
{txt}{space 14}_cons {c |}{col 21}{res}{space 2}  .589764{col 33}{space 2} .0378309{col 44}{space 1}   15.59{col 53}{space 3}0.000{col 61}{space 4} .5154316{col 74}{space 3} .6640964
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5300
                                                       {txt}F( 21,   486) ={res}    4.96
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0498
                                                       {txt}Root MSE      = {res} .25225

{txt}{ralign 85:(Std. Err. adjusted for {res:487} clusters in psu_new)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}policy_pref_milit~y{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}treat_militancy {c |}{col 21}{res}{space 2} .0312537{col 33}{space 2} .0406487{col 44}{space 1}    0.77{col 53}{space 3}0.442{col 61}{space 4}-.0486153{col 74}{space 3} .1111227
{txt}{space 16}n01 {c |}{col 21}{res}{space 2} .0837387{col 33}{space 2} .0450739{col 44}{space 1}    1.86{col 53}{space 3}0.064{col 61}{space 4}-.0048252{col 74}{space 3} .1723026
{txt}{space 16}n10 {c |}{col 21}{res}{space 2} .0078635{col 33}{space 2} .0480942{col 44}{space 1}    0.16{col 53}{space 3}0.870{col 61}{space 4}-.0866348{col 74}{space 3} .1023618
{txt}{space 16}n11 {c |}{col 21}{res}{space 2} .1051798{col 33}{space 2} .0448272{col 44}{space 1}    2.35{col 53}{space 3}0.019{col 61}{space 4} .0171007{col 74}{space 3} .1932589
{txt}n01_treat_militancy {c |}{col 21}{res}{space 2}-.0950827{col 33}{space 2} .0538882{col 44}{space 1}   -1.76{col 53}{space 3}0.078{col 61}{space 4}-.2009653{col 74}{space 3}    .0108
{txt}n10_treat_militancy {c |}{col 21}{res}{space 2}-.0155924{col 33}{space 2} .0557289{col 44}{space 1}   -0.28{col 53}{space 3}0.780{col 61}{space 4}-.1250918{col 74}{space 3}  .093907
{txt}n11_treat_militancy {c |}{col 21}{res}{space 2}-.1450263{col 33}{space 2} .0538995{col 44}{space 1}   -2.69{col 53}{space 3}0.007{col 61}{space 4}-.2509311{col 74}{space 3}-.0391215
{txt}{space 11}gender_z {c |}{col 21}{res}{space 2} .0231532{col 33}{space 2} .0196103{col 44}{space 1}    1.18{col 53}{space 3}0.238{col 61}{space 4}-.0153781{col 74}{space 3} .0616846
{txt}{space 12}headh_z {c |}{col 21}{res}{space 2} .0001781{col 33}{space 2} .0132938{col 44}{space 1}    0.01{col 53}{space 3}0.989{col 61}{space 4}-.0259422{col 74}{space 3} .0262985
{txt}{space 14}age_z {c |}{col 21}{res}{space 2} .0189449{col 33}{space 2} .0301364{col 44}{space 1}    0.63{col 53}{space 3}0.530{col 61}{space 4}-.0402689{col 74}{space 3} .0781586
{txt}{space 13}read_z {c |}{col 21}{res}{space 2}-.0300587{col 33}{space 2} .0170713{col 44}{space 1}   -1.76{col 53}{space 3}0.079{col 61}{space 4}-.0636014{col 74}{space 3}  .003484
{txt}{space 13}math_z {c |}{col 21}{res}{space 2} .0829417{col 33}{space 2} .0185324{col 44}{space 1}    4.48{col 53}{space 3}0.000{col 61}{space 4} .0465282{col 74}{space 3} .1193552
{txt}{space 13}educ_z {c |}{col 21}{res}{space 2} .0357789{col 33}{space 2} .0282312{col 44}{space 1}    1.27{col 53}{space 3}0.206{col 61}{space 4}-.0196914{col 74}{space 3} .0912492
{txt}{space 6}houseexpend_z {c |}{col 21}{res}{space 2} .2111513{col 33}{space 2} .0577663{col 44}{space 1}    3.66{col 53}{space 3}0.000{col 61}{space 4} .0976489{col 74}{space 3} .3246538
{txt}{space 7}assetindex_z {c |}{col 21}{res}{space 2}-.0131742{col 33}{space 2} .0478886{col 44}{space 1}   -0.28{col 53}{space 3}0.783{col 61}{space 4}-.1072686{col 74}{space 3} .0809201
{txt}{space 9}headh_miss {c |}{col 21}{res}{space 2} -.069966{col 33}{space 2} .0557479{col 44}{space 1}   -1.26{col 53}{space 3}0.210{col 61}{space 4}-.1795026{col 74}{space 3} .0395706
{txt}{space 11}age_miss {c |}{col 21}{res}{space 2} .1288185{col 33}{space 2} .0642848{col 44}{space 1}    2.00{col 53}{space 3}0.046{col 61}{space 4} .0025081{col 74}{space 3} .2551289
{txt}{space 10}read_miss {c |}{col 21}{res}{space 2} -.083821{col 33}{space 2} .0420309{col 44}{space 1}   -1.99{col 53}{space 3}0.047{col 61}{space 4}-.1664057{col 74}{space 3}-.0012362
{txt}{space 10}math_miss {c |}{col 21}{res}{space 2} .0920102{col 33}{space 2} .0228245{col 44}{space 1}    4.03{col 53}{space 3}0.000{col 61}{space 4} .0471633{col 74}{space 3} .1368571
{txt}{space 10}educ_miss {c |}{col 21}{res}{space 2}  .175133{col 33}{space 2} .0678549{col 44}{space 1}    2.58{col 53}{space 3}0.010{col 61}{space 4} .0418079{col 74}{space 3} .3084582
{txt}{space 3}houseexpend_miss {c |}{col 21}{res}{space 2} .1059681{col 33}{space 2} .0274379{col 44}{space 1}    3.86{col 53}{space 3}0.000{col 61}{space 4} .0520564{col 74}{space 3} .1598797
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .4799184{col 33}{space 2} .0448539{col 44}{space 1}   10.70{col 53}{space 3}0.000{col 61}{space 4} .3917869{col 74}{space 3} .5680498
{txt}{hline 20}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: treat_militancy omitted because of collinearity
{res}
{txt}Linear regression, absorbing indicators{col 51}Number of obs{col 67}= {res}      5303
{txt}{col 51}F({res}   6{txt},{res}     66{txt}){col 67}= {res}      1.41
{txt}{col 51}Prob > F{col 67}= {res}    0.2255
{txt}{col 51}R-squared{col 67}= {res}    0.1354
{txt}{col 51}Adj R-squared{col 67}= {res}    0.1330
{txt}{col 51}Root MSE{col 67}= {res}    0.2405

{txt}{ralign 85:(Std. Err. adjusted for {res:67} clusters in a7)}
{hline 20}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 21}{c |}{col 33}    Robust
{col 1}policy_pref_milit~y{col 21}{c |}      Coef.{col 33}   Std. Err.{col 45}      t{col 53}   P>|t|{col 61}     [95% Con{col 74}f. Interval]
{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 4}treat_militancy {c |}{col 21}{res}{space 2}        0{col 33}{txt}  (omitted)
{space 16}n01 {c |}{col 21}{res}{space 2} .0492285{col 33}{space 2} .0307948{col 44}{space 1}    1.60{col 53}{space 3}0.115{col 61}{space 4}-.0122553{col 74}{space 3} .1107123
{txt}{space 16}n10 {c |}{col 21}{res}{space 2}-.0004423{col 33}{space 2} .0397151{col 44}{space 1}   -0.01{col 53}{space 3}0.991{col 61}{space 4}-.0797361{col 74}{space 3} .0788514
{txt}{space 16}n11 {c |}{col 21}{res}{space 2} .0754755{col 33}{space 2} .0367839{col 44}{space 1}    2.05{col 53}{space 3}0.044{col 61}{space 4} .0020341{col 74}{space 3} .1489168
{txt}n01_treat_militancy {c |}{col 21}{res}{space 2}-.0913688{col 33}{space 2}  .051239{col 44}{space 1}   -1.78{col 53}{space 3}0.079{col 61}{space 4}-.1936708{col 74}{space 3} .0109331
{txt}n10_treat_militancy {c |}{col 21}{res}{space 2}-.0056106{col 33}{space 2} .0444743{col 44}{space 1}   -0.13{col 53}{space 3}0.900{col 61}{space 4}-.0944063{col 74}{space 3} .0831852
{txt}n11_treat_militancy {c |}{col 21}{res}{space 2}-.1234667{col 33}{space 2} .0476683{col 44}{space 1}   -2.59{col 53}{space 3}0.012{col 61}{space 4}-.2186395{col 74}{space 3}-.0282939
{txt}{space 14}_cons {c |}{col 21}{res}{space 2} .6289103{col 33}{space 2} .0163867{col 44}{space 1}   38.38{col 53}{space 3}0.000{col 61}{space 4} .5961931{col 74}{space 3} .6616274
{txt}{hline 20}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
          treatprov {c |}   absorbed                                      (10 categories)

{com}. 
. 
. // APPENDIX TABLE 5: Effects of Experimental Treatments by Observed Poverty on Support for Militant Groups
. 
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' poverty lowexp20_urprov poverty_treat_`x' lowexp20_urprov_`x' lowexp20_urprov_pov lowexp20_urprov_pov_`x', cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' poverty lowexp20_urprov poverty_treat_`x' lowexp20_urprov_`x' lowexp20_urprov_pov lowexp20_urprov_pov_`x' gender_z headh_z age_z read_z math_z educ_z assetindex_z headh_miss age_miss read_miss math_miss educ_miss, cluster(psu_new)
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  7,   952) ={res}    4.03
                                                       {txt}Prob > F      = {res} 0.0002
                                                       {txt}R-squared     = {res} 0.0101
                                                       {txt}Root MSE      = {res}  .2539

{txt}{ralign 95:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}        policy_pref_militancy{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}treat_militancy {c |}{col 31}{res}{space 2} .0300644{col 43}{space 2} .0212136{col 54}{space 1}    1.42{col 63}{space 3}0.157{col 71}{space 4}-.0115665{col 84}{space 3} .0716952
{txt}{space 22}poverty {c |}{col 31}{res}{space 2} .0420142{col 43}{space 2} .0250003{col 54}{space 1}    1.68{col 63}{space 3}0.093{col 71}{space 4}-.0070478{col 84}{space 3} .0910763
{txt}{space 14}lowexp20_urprov {c |}{col 31}{res}{space 2} .0091648{col 43}{space 2} .0207159{col 54}{space 1}    0.44{col 63}{space 3}0.658{col 71}{space 4}-.0314894{col 84}{space 3} .0498189
{txt}{space 6}poverty_treat_militancy {c |}{col 31}{res}{space 2}-.0617926{col 43}{space 2} .0297218{col 54}{space 1}   -2.08{col 63}{space 3}0.038{col 71}{space 4}-.1201204{col 84}{space 3}-.0034648
{txt}{space 4}lowexp20_urprov_militancy {c |}{col 31}{res}{space 2}-.0621491{col 43}{space 2} .0272186{col 54}{space 1}   -2.28{col 63}{space 3}0.023{col 71}{space 4}-.1155645{col 84}{space 3}-.0087337
{txt}{space 10}lowexp20_urprov_pov {c |}{col 31}{res}{space 2} -.051528{col 43}{space 2}  .032367{col 54}{space 1}   -1.59{col 63}{space 3}0.112{col 71}{space 4} -.115047{col 84}{space 3}  .011991
{txt}lowexp20_urprov_pov_militancy {c |}{col 31}{res}{space 2} .0406938{col 43}{space 2} .0411869{col 54}{space 1}    0.99{col 63}{space 3}0.323{col 71}{space 4}-.0401337{col 84}{space 3} .1215214
{txt}{space 24}_cons {c |}{col 31}{res}{space 2} .6205227{col 43}{space 2}  .018301{col 54}{space 1}   33.91{col 63}{space 3}0.000{col 71}{space 4} .5846077{col 84}{space 3} .6564378
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 19,   952) ={res}    6.33
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0333
                                                       {txt}Root MSE      = {res} .25106

{txt}{ralign 95:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 30}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 31}{c |}{col 43}    Robust
{col 1}        policy_pref_militancy{col 31}{c |}      Coef.{col 43}   Std. Err.{col 55}      t{col 63}   P>|t|{col 71}     [95% Con{col 84}f. Interval]
{hline 30}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 14}treat_militancy {c |}{col 31}{res}{space 2} .0221762{col 43}{space 2} .0207889{col 54}{space 1}    1.07{col 63}{space 3}0.286{col 71}{space 4}-.0186211{col 84}{space 3} .0629735
{txt}{space 22}poverty {c |}{col 31}{res}{space 2} .0367789{col 43}{space 2} .0242984{col 54}{space 1}    1.51{col 63}{space 3}0.130{col 71}{space 4}-.0109058{col 84}{space 3} .0844636
{txt}{space 14}lowexp20_urprov {c |}{col 31}{res}{space 2} .0204762{col 43}{space 2} .0195691{col 54}{space 1}    1.05{col 63}{space 3}0.296{col 71}{space 4}-.0179274{col 84}{space 3} .0588799
{txt}{space 6}poverty_treat_militancy {c |}{col 31}{res}{space 2}-.0579494{col 43}{space 2} .0288927{col 54}{space 1}   -2.01{col 63}{space 3}0.045{col 71}{space 4}-.1146501{col 84}{space 3}-.0012487
{txt}{space 4}lowexp20_urprov_militancy {c |}{col 31}{res}{space 2}-.0616956{col 43}{space 2} .0260038{col 54}{space 1}   -2.37{col 63}{space 3}0.018{col 71}{space 4}-.1127271{col 84}{space 3}-.0106642
{txt}{space 10}lowexp20_urprov_pov {c |}{col 31}{res}{space 2} -.054613{col 43}{space 2} .0305491{col 54}{space 1}   -1.79{col 63}{space 3}0.074{col 71}{space 4}-.1145643{col 84}{space 3} .0053383
{txt}lowexp20_urprov_pov_militancy {c |}{col 31}{res}{space 2} .0442143{col 43}{space 2} .0394067{col 54}{space 1}    1.12{col 63}{space 3}0.262{col 71}{space 4}-.0331198{col 84}{space 3} .1215484
{txt}{space 21}gender_z {c |}{col 31}{res}{space 2} .0260407{col 43}{space 2} .0136943{col 54}{space 1}    1.90{col 63}{space 3}0.058{col 71}{space 4}-.0008338{col 84}{space 3} .0529152
{txt}{space 22}headh_z {c |}{col 31}{res}{space 2}-.0066572{col 43}{space 2} .0095369{col 54}{space 1}   -0.70{col 63}{space 3}0.485{col 71}{space 4}-.0253729{col 84}{space 3} .0120586
{txt}{space 24}age_z {c |}{col 31}{res}{space 2} .0371117{col 43}{space 2} .0215587{col 54}{space 1}    1.72{col 63}{space 3}0.085{col 71}{space 4}-.0051963{col 84}{space 3} .0794198
{txt}{space 23}read_z {c |}{col 31}{res}{space 2}-.0220843{col 43}{space 2} .0121869{col 54}{space 1}   -1.81{col 63}{space 3}0.070{col 71}{space 4}-.0460005{col 84}{space 3}  .001832
{txt}{space 23}math_z {c |}{col 31}{res}{space 2} .0653661{col 43}{space 2} .0139023{col 54}{space 1}    4.70{col 63}{space 3}0.000{col 71}{space 4} .0380835{col 84}{space 3} .0926488
{txt}{space 23}educ_z {c |}{col 31}{res}{space 2} .0703342{col 43}{space 2} .0198241{col 54}{space 1}    3.55{col 63}{space 3}0.000{col 71}{space 4} .0314302{col 84}{space 3} .1092382
{txt}{space 17}assetindex_z {c |}{col 31}{res}{space 2}-.0291135{col 43}{space 2} .0355021{col 54}{space 1}   -0.82{col 63}{space 3}0.412{col 71}{space 4} -.098785{col 84}{space 3} .0405579
{txt}{space 19}headh_miss {c |}{col 31}{res}{space 2}-.0422204{col 43}{space 2}  .049702{col 54}{space 1}   -0.85{col 63}{space 3}0.396{col 71}{space 4}-.1397586{col 84}{space 3} .0553178
{txt}{space 21}age_miss {c |}{col 31}{res}{space 2} .1994566{col 43}{space 2} .0533787{col 54}{space 1}    3.74{col 63}{space 3}0.000{col 71}{space 4}  .094703{col 84}{space 3} .3042102
{txt}{space 20}read_miss {c |}{col 31}{res}{space 2}-.0805392{col 43}{space 2}  .039854{col 54}{space 1}   -2.02{col 63}{space 3}0.044{col 71}{space 4} -.158751{col 84}{space 3}-.0023274
{txt}{space 20}math_miss {c |}{col 31}{res}{space 2} .0908406{col 43}{space 2} .0171614{col 54}{space 1}    5.29{col 63}{space 3}0.000{col 71}{space 4}  .057162{col 84}{space 3} .1245193
{txt}{space 20}educ_miss {c |}{col 31}{res}{space 2} .1334032{col 43}{space 2} .0570498{col 54}{space 1}    2.34{col 63}{space 3}0.020{col 71}{space 4} .0214454{col 84}{space 3}  .245361
{txt}{space 24}_cons {c |}{col 31}{res}{space 2} .5554812{col 43}{space 2} .0269135{col 54}{space 1}   20.64{col 63}{space 3}0.000{col 71}{space 4} .5026646{col 84}{space 3} .6082979
{txt}{hline 30}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' natviol lowexp20_urprov natviol_treat_`x' lowexp20_urprov_`x' lowexp20_urprov_viol lowexp20_urprov_viol_`x', cluster(psu_new)
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' natviol lowexp20_urprov natviol_treat_`x' lowexp20_urprov_`x' lowexp20_urprov_viol lowexp20_urprov_viol_`x' gender_z headh_z age_z read_z math_z educ_z assetindex_z headh_miss age_miss read_miss math_miss educ_miss, cluster(psu_new)
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}    5300
                                                       {txt}F(  7,   486) ={res}    3.86
                                                       {txt}Prob > F      = {res} 0.0004
                                                       {txt}R-squared     = {res} 0.0237
                                                       {txt}Root MSE      = {res} .25536

{txt}{ralign 96:(Std. Err. adjusted for {res:487} clusters in psu_new)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}         policy_pref_militancy{col 32}{c |}      Coef.{col 44}   Std. Err.{col 56}      t{col 64}   P>|t|{col 72}     [95% Con{col 85}f. Interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat_militancy {c |}{col 32}{res}{space 2} .0285432{col 44}{space 2} .0299442{col 55}{space 1}    0.95{col 64}{space 3}0.341{col 72}{space 4} -.030293{col 85}{space 3} .0873793
{txt}{space 23}natviol {c |}{col 32}{res}{space 2} .0942551{col 44}{space 2} .0325173{col 55}{space 1}    2.90{col 64}{space 3}0.004{col 72}{space 4} .0303634{col 85}{space 3} .1581469
{txt}{space 15}lowexp20_urprov {c |}{col 32}{res}{space 2}-.0159418{col 44}{space 2} .0324281{col 55}{space 1}   -0.49{col 64}{space 3}0.623{col 72}{space 4}-.0796583{col 85}{space 3} .0477747
{txt}{space 7}natviol_treat_militancy {c |}{col 32}{res}{space 2}-.0982924{col 44}{space 2} .0398839{col 55}{space 1}   -2.46{col 64}{space 3}0.014{col 72}{space 4}-.1766585{col 85}{space 3}-.0199263
{txt}{space 5}lowexp20_urprov_militancy {c |}{col 32}{res}{space 2}-.0130692{col 44}{space 2} .0383867{col 55}{space 1}   -0.34{col 64}{space 3}0.734{col 72}{space 4}-.0884937{col 85}{space 3} .0623553
{txt}{space 10}lowexp20_urprov_viol {c |}{col 32}{res}{space 2}-.0345649{col 44}{space 2} .0424152{col 55}{space 1}   -0.81{col 64}{space 3}0.416{col 72}{space 4}-.1179048{col 85}{space 3}  .048775
{txt}lowexp20_urprov_viol_militancy {c |}{col 32}{res}{space 2}-.0463373{col 44}{space 2} .0568303{col 55}{space 1}   -0.82{col 64}{space 3}0.415{col 72}{space 4}-.1580007{col 85}{space 3}  .065326
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .6005773{col 44}{space 2} .0255161{col 55}{space 1}   23.54{col 64}{space 3}0.000{col 72}{space 4} .5504417{col 85}{space 3} .6507128
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}    5300
                                                       {txt}F( 19,   486) ={res}    4.99
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0498
                                                       {txt}Root MSE      = {res} .25221

{txt}{ralign 96:(Std. Err. adjusted for {res:487} clusters in psu_new)}
{hline 31}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 32}{c |}{col 44}    Robust
{col 1}         policy_pref_militancy{col 32}{c |}      Coef.{col 44}   Std. Err.{col 56}      t{col 64}   P>|t|{col 72}     [95% Con{col 85}f. Interval]
{hline 31}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 15}treat_militancy {c |}{col 32}{res}{space 2} .0250408{col 44}{space 2} .0288113{col 55}{space 1}    0.87{col 64}{space 3}0.385{col 72}{space 4}-.0315693{col 85}{space 3}  .081651
{txt}{space 23}natviol {c |}{col 32}{res}{space 2} .0966298{col 44}{space 2} .0315472{col 55}{space 1}    3.06{col 64}{space 3}0.002{col 72}{space 4}  .034644{col 85}{space 3} .1586156
{txt}{space 15}lowexp20_urprov {c |}{col 32}{res}{space 2}-.0066723{col 44}{space 2} .0321329{col 55}{space 1}   -0.21{col 64}{space 3}0.836{col 72}{space 4}-.0698089{col 85}{space 3} .0564643
{txt}{space 7}natviol_treat_militancy {c |}{col 32}{res}{space 2}-.1005319{col 44}{space 2} .0388257{col 55}{space 1}   -2.59{col 64}{space 3}0.010{col 72}{space 4}-.1768189{col 85}{space 3}-.0242449
{txt}{space 5}lowexp20_urprov_militancy {c |}{col 32}{res}{space 2}-.0099056{col 44}{space 2}  .036611{col 55}{space 1}   -0.27{col 64}{space 3}0.787{col 72}{space 4}-.0818411{col 85}{space 3} .0620298
{txt}{space 10}lowexp20_urprov_viol {c |}{col 32}{res}{space 2}-.0328028{col 44}{space 2} .0403664{col 55}{space 1}   -0.81{col 64}{space 3}0.417{col 72}{space 4} -.112117{col 85}{space 3} .0465115
{txt}lowexp20_urprov_viol_militancy {c |}{col 32}{res}{space 2}-.0508953{col 44}{space 2} .0538553{col 55}{space 1}   -0.95{col 64}{space 3}0.345{col 72}{space 4}-.1567132{col 85}{space 3} .0549226
{txt}{space 22}gender_z {c |}{col 32}{res}{space 2} .0236391{col 44}{space 2} .0196245{col 55}{space 1}    1.20{col 64}{space 3}0.229{col 72}{space 4}-.0149203{col 85}{space 3} .0621984
{txt}{space 23}headh_z {c |}{col 32}{res}{space 2} -.002111{col 44}{space 2} .0134814{col 55}{space 1}   -0.16{col 64}{space 3}0.876{col 72}{space 4}   -.0286{col 85}{space 3} .0243779
{txt}{space 25}age_z {c |}{col 32}{res}{space 2} .0281553{col 44}{space 2} .0303497{col 55}{space 1}    0.93{col 64}{space 3}0.354{col 72}{space 4}-.0314776{col 85}{space 3} .0877882
{txt}{space 24}read_z {c |}{col 32}{res}{space 2}-.0298769{col 44}{space 2} .0169876{col 55}{space 1}   -1.76{col 64}{space 3}0.079{col 72}{space 4}-.0632551{col 85}{space 3} .0035013
{txt}{space 24}math_z {c |}{col 32}{res}{space 2}  .081684{col 44}{space 2} .0187711{col 55}{space 1}    4.35{col 64}{space 3}0.000{col 72}{space 4} .0448015{col 85}{space 3} .1185665
{txt}{space 24}educ_z {c |}{col 32}{res}{space 2} .0533965{col 44}{space 2} .0275679{col 55}{space 1}    1.94{col 64}{space 3}0.053{col 72}{space 4}-.0007705{col 85}{space 3} .1075636
{txt}{space 18}assetindex_z {c |}{col 32}{res}{space 2}-.0030463{col 44}{space 2} .0466008{col 55}{space 1}   -0.07{col 64}{space 3}0.948{col 72}{space 4}-.0946103{col 85}{space 3} .0885177
{txt}{space 20}headh_miss {c |}{col 32}{res}{space 2}-.0709616{col 44}{space 2}  .055681{col 55}{space 1}   -1.27{col 64}{space 3}0.203{col 72}{space 4}-.1803668{col 85}{space 3} .0384436
{txt}{space 22}age_miss {c |}{col 32}{res}{space 2} .1475457{col 44}{space 2} .0604624{col 55}{space 1}    2.44{col 64}{space 3}0.015{col 72}{space 4} .0287458{col 85}{space 3} .2663456
{txt}{space 21}read_miss {c |}{col 32}{res}{space 2}-.0796309{col 44}{space 2} .0409579{col 55}{space 1}   -1.94{col 64}{space 3}0.052{col 72}{space 4}-.1601074{col 85}{space 3} .0008456
{txt}{space 21}math_miss {c |}{col 32}{res}{space 2} .0891778{col 44}{space 2} .0234064{col 55}{space 1}    3.81{col 64}{space 3}0.000{col 72}{space 4} .0431875{col 85}{space 3} .1351681
{txt}{space 21}educ_miss {c |}{col 32}{res}{space 2} .1964644{col 44}{space 2} .0713417{col 55}{space 1}    2.75{col 64}{space 3}0.006{col 72}{space 4} .0562881{col 85}{space 3} .3366408
{txt}{space 25}_cons {c |}{col 32}{res}{space 2} .5166965{col 44}{space 2} .0375551{col 55}{space 1}   13.76{col 64}{space 3}0.000{col 72}{space 4} .4429061{col 85}{space 3}  .590487
{txt}{hline 31}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. // APPENDIX TABLE 6: Effects of Poverty Experiment on Support for Militant Groups when Controlling for Potential Confounding Interactions
. 
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' educ_z educ_treat_`x' educ_miss, cluster(psu_new) 
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' educ_z educ_treat_`x' educ_miss *_z *_miss, cluster(psu_new)
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  6,   952) ={res}    7.72
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0147
                                                       {txt}Root MSE      = {res} .25329

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0133958{col 37}{space 2} .0223396{col 48}{space 1}    0.60{col 57}{space 3}0.549{col 65}{space 4}-.0304448{col 78}{space 3} .0572364
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0269716{col 37}{space 2} .0231732{col 48}{space 1}    1.16{col 57}{space 3}0.245{col 65}{space 4}-.0185049{col 78}{space 3}  .072448
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0469448{col 37}{space 2} .0282172{col 48}{space 1}   -1.66{col 57}{space 3}0.097{col 65}{space 4}-.1023199{col 78}{space 3} .0084304
{txt}{space 17}educ_z {c |}{col 25}{res}{space 2} .1021897{col 37}{space 2} .0243719{col 48}{space 1}    4.19{col 57}{space 3}0.000{col 65}{space 4} .0543608{col 78}{space 3} .1500186
{txt}{space 3}educ_treat_militancy {c |}{col 25}{res}{space 2} -.014019{col 37}{space 2} .0306535{col 48}{space 1}   -0.46{col 57}{space 3}0.648{col 65}{space 4}-.0741752{col 78}{space 3} .0461372
{txt}{space 14}educ_miss {c |}{col 25}{res}{space 2} .1442418{col 37}{space 2} .0556879{col 48}{space 1}    2.59{col 57}{space 3}0.010{col 65}{space 4} .0349567{col 78}{space 3}  .253527
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5973195{col 37}{space 2} .0184087{col 48}{space 1}   32.45{col 57}{space 3}0.000{col 65}{space 4} .5611932{col 78}{space 3} .6334459
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: educ_z omitted because of collinearity
note: educ_miss omitted because of collinearity

Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 18,   952) ={res}    7.69
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0369
                                                       {txt}Root MSE      = {res} .25057

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0104668{col 37}{space 2} .0222689{col 48}{space 1}    0.47{col 57}{space 3}0.638{col 65}{space 4} -.033235{col 78}{space 3} .0541685
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0218463{col 37}{space 2} .0227319{col 48}{space 1}    0.96{col 57}{space 3}0.337{col 65}{space 4}-.0227642{col 78}{space 3} .0664567
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0457547{col 37}{space 2} .0275895{col 48}{space 1}   -1.66{col 57}{space 3}0.098{col 65}{space 4} -.099898{col 78}{space 3} .0083887
{txt}{space 17}educ_z {c |}{col 25}{res}{space 2} .0653532{col 37}{space 2} .0271544{col 48}{space 1}    2.41{col 57}{space 3}0.016{col 65}{space 4} .0120637{col 78}{space 3} .1186426
{txt}{space 3}educ_treat_militancy {c |}{col 25}{res}{space 2}-.0156266{col 37}{space 2} .0299703{col 48}{space 1}   -0.52{col 57}{space 3}0.602{col 65}{space 4}-.0744422{col 78}{space 3}  .043189
{txt}{space 14}educ_miss {c |}{col 25}{res}{space 2} .1229486{col 37}{space 2} .0566817{col 48}{space 1}    2.17{col 57}{space 3}0.030{col 65}{space 4}  .011713{col 78}{space 3} .2341842
{txt}{space 15}gender_z {c |}{col 25}{res}{space 2} .0265548{col 37}{space 2} .0135802{col 48}{space 1}    1.96{col 57}{space 3}0.051{col 65}{space 4}-.0000959{col 78}{space 3} .0532055
{txt}{space 16}headh_z {c |}{col 25}{res}{space 2}-.0045646{col 37}{space 2} .0094306{col 48}{space 1}   -0.48{col 57}{space 3}0.628{col 65}{space 4}-.0230718{col 78}{space 3} .0139427
{txt}{space 18}age_z {c |}{col 25}{res}{space 2} .0276589{col 37}{space 2} .0214517{col 48}{space 1}    1.29{col 57}{space 3}0.198{col 65}{space 4}-.0144392{col 78}{space 3}  .069757
{txt}{space 17}read_z {c |}{col 25}{res}{space 2}-.0203782{col 37}{space 2} .0122213{col 48}{space 1}   -1.67{col 57}{space 3}0.096{col 65}{space 4}-.0443619{col 78}{space 3} .0036056
{txt}{space 17}math_z {c |}{col 25}{res}{space 2} .0647894{col 37}{space 2} .0139244{col 48}{space 1}    4.65{col 57}{space 3}0.000{col 65}{space 4} .0374634{col 78}{space 3} .0921154
{txt}{space 17}educ_z {c |}{col 25}{res}{space 2}        0{col 37}{txt}  (omitted)
{space 10}houseexpend_z {c |}{col 25}{res}{space 2}  .233389{col 37}{space 2} .0417514{col 48}{space 1}    5.59{col 57}{space 3}0.000{col 65}{space 4} .1514536{col 78}{space 3} .3153243
{txt}{space 11}assetindex_z {c |}{col 25}{res}{space 2}-.0456793{col 37}{space 2} .0366485{col 48}{space 1}   -1.25{col 57}{space 3}0.213{col 65}{space 4}-.1176005{col 78}{space 3} .0262419
{txt}{space 13}headh_miss {c |}{col 25}{res}{space 2}-.0358088{col 37}{space 2} .0495539{col 48}{space 1}   -0.72{col 57}{space 3}0.470{col 65}{space 4}-.1330563{col 78}{space 3} .0614388
{txt}{space 15}age_miss {c |}{col 25}{res}{space 2} .1801909{col 37}{space 2} .0517773{col 48}{space 1}    3.48{col 57}{space 3}0.001{col 65}{space 4} .0785802{col 78}{space 3} .2818017
{txt}{space 14}read_miss {c |}{col 25}{res}{space 2}-.0834971{col 37}{space 2} .0401569{col 48}{space 1}   -2.08{col 57}{space 3}0.038{col 65}{space 4}-.1623035{col 78}{space 3}-.0046908
{txt}{space 14}math_miss {c |}{col 25}{res}{space 2} .0864586{col 37}{space 2} .0170768{col 48}{space 1}    5.06{col 57}{space 3}0.000{col 65}{space 4} .0529461{col 78}{space 3} .1199711
{txt}{space 14}educ_miss {c |}{col 25}{res}{space 2}        0{col 37}{txt}  (omitted)
{space 7}houseexpend_miss {c |}{col 25}{res}{space 2} .0770658{col 37}{space 2} .0184103{col 48}{space 1}    4.19{col 57}{space 3}0.000{col 65}{space 4} .0409363{col 78}{space 3} .1131953
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5287373{col 37}{space 2}  .026182{col 48}{space 1}   20.19{col 57}{space 3}0.000{col 65}{space 4} .4773562{col 78}{space 3} .5801184
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' read_z read_treat_`x' read_miss, cluster(psu_new) 
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' read_z read_treat_`x' read_miss *_z *_miss, cluster(psu_new)
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  6,   952) ={res}    3.85
                                                       {txt}Prob > F      = {res} 0.0008
                                                       {txt}R-squared     = {res} 0.0071
                                                       {txt}Root MSE      = {res} .25427

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0261473{col 37}{space 2} .0232266{col 48}{space 1}    1.13{col 57}{space 3}0.261{col 65}{space 4} -.019434{col 78}{space 3} .0717286
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0284509{col 37}{space 2} .0232662{col 48}{space 1}    1.22{col 57}{space 3}0.222{col 65}{space 4}-.0172081{col 78}{space 3} .0741099
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0498302{col 37}{space 2} .0283766{col 48}{space 1}   -1.76{col 57}{space 3}0.079{col 65}{space 4} -.105518{col 78}{space 3} .0058577
{txt}{space 17}read_z {c |}{col 25}{res}{space 2} .0496874{col 37}{space 2} .0152612{col 48}{space 1}    3.26{col 57}{space 3}0.001{col 65}{space 4} .0197379{col 78}{space 3} .0796369
{txt}{space 3}read_treat_militancy {c |}{col 25}{res}{space 2}-.0235811{col 37}{space 2} .0188316{col 48}{space 1}   -1.25{col 57}{space 3}0.211{col 65}{space 4}-.0605372{col 78}{space 3} .0133751
{txt}{space 14}read_miss {c |}{col 25}{res}{space 2} -.048755{col 37}{space 2}  .040831{col 48}{space 1}   -1.19{col 57}{space 3}0.233{col 65}{space 4}-.1288841{col 78}{space 3} .0313741
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}  .597714{col 37}{space 2}  .019264{col 48}{space 1}   31.03{col 57}{space 3}0.000{col 65}{space 4} .5599091{col 78}{space 3} .6355188
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}note: read_z omitted because of collinearity
note: read_miss omitted because of collinearity

Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 18,   952) ={res}    7.63
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0371
                                                       {txt}Root MSE      = {res} .25054

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0165526{col 37}{space 2} .0228289{col 48}{space 1}    0.73{col 57}{space 3}0.469{col 65}{space 4}-.0282481{col 78}{space 3} .0613533
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0215566{col 37}{space 2} .0227204{col 48}{space 1}    0.95{col 57}{space 3}0.343{col 65}{space 4}-.0230312{col 78}{space 3} .0661445
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2} -.045442{col 37}{space 2} .0275747{col 48}{space 1}   -1.65{col 57}{space 3}0.100{col 65}{space 4}-.0995562{col 78}{space 3} .0086723
{txt}{space 17}read_z {c |}{col 25}{res}{space 2} -.005513{col 37}{space 2} .0172107{col 48}{space 1}   -0.32{col 57}{space 3}0.749{col 65}{space 4}-.0392883{col 78}{space 3} .0282623
{txt}{space 3}read_treat_militancy {c |}{col 25}{res}{space 2} -.019473{col 37}{space 2} .0183564{col 48}{space 1}   -1.06{col 57}{space 3}0.289{col 65}{space 4}-.0554968{col 78}{space 3} .0165507
{txt}{space 14}read_miss {c |}{col 25}{res}{space 2}-.0846353{col 37}{space 2} .0402592{col 48}{space 1}   -2.10{col 57}{space 3}0.036{col 65}{space 4}-.1636423{col 78}{space 3}-.0056282
{txt}{space 15}gender_z {c |}{col 25}{res}{space 2} .0265633{col 37}{space 2} .0135854{col 48}{space 1}    1.96{col 57}{space 3}0.051{col 65}{space 4}-.0000975{col 78}{space 3}  .053224
{txt}{space 16}headh_z {c |}{col 25}{res}{space 2} -.004789{col 37}{space 2} .0094324{col 48}{space 1}   -0.51{col 57}{space 3}0.612{col 65}{space 4}-.0232998{col 78}{space 3} .0137218
{txt}{space 18}age_z {c |}{col 25}{res}{space 2} .0278414{col 37}{space 2} .0214545{col 48}{space 1}    1.30{col 57}{space 3}0.195{col 65}{space 4}-.0142621{col 78}{space 3} .0699449
{txt}{space 17}read_z {c |}{col 25}{res}{space 2}        0{col 37}{txt}  (omitted)
{space 17}math_z {c |}{col 25}{res}{space 2} .0648274{col 37}{space 2} .0139287{col 48}{space 1}    4.65{col 57}{space 3}0.000{col 65}{space 4} .0374928{col 78}{space 3}  .092162
{txt}{space 17}educ_z {c |}{col 25}{res}{space 2} .0529843{col 37}{space 2} .0198419{col 48}{space 1}    2.67{col 57}{space 3}0.008{col 65}{space 4} .0140453{col 78}{space 3} .0919232
{txt}{space 10}houseexpend_z {c |}{col 25}{res}{space 2} .2333856{col 37}{space 2} .0417153{col 48}{space 1}    5.59{col 57}{space 3}0.000{col 65}{space 4} .1515211{col 78}{space 3} .3152501
{txt}{space 11}assetindex_z {c |}{col 25}{res}{space 2}-.0455805{col 37}{space 2} .0366221{col 48}{space 1}   -1.24{col 57}{space 3}0.214{col 65}{space 4}-.1174499{col 78}{space 3} .0262888
{txt}{space 13}headh_miss {c |}{col 25}{res}{space 2}-.0348038{col 37}{space 2} .0494805{col 48}{space 1}   -0.70{col 57}{space 3}0.482{col 65}{space 4}-.1319072{col 78}{space 3} .0622997
{txt}{space 15}age_miss {c |}{col 25}{res}{space 2} .1799126{col 37}{space 2} .0516906{col 48}{space 1}    3.48{col 57}{space 3}0.001{col 65}{space 4}  .078472{col 78}{space 3} .2813532
{txt}{space 14}read_miss {c |}{col 25}{res}{space 2}        0{col 37}{txt}  (omitted)
{space 14}math_miss {c |}{col 25}{res}{space 2} .0864904{col 37}{space 2} .0170845{col 48}{space 1}    5.06{col 57}{space 3}0.000{col 65}{space 4} .0529628{col 78}{space 3} .1200181
{txt}{space 14}educ_miss {c |}{col 25}{res}{space 2} .1218664{col 37}{space 2} .0565598{col 48}{space 1}    2.15{col 57}{space 3}0.031{col 65}{space 4} .0108701{col 78}{space 3} .2328626
{txt}{space 7}houseexpend_miss {c |}{col 25}{res}{space 2} .0768118{col 37}{space 2}  .018422{col 48}{space 1}    4.17{col 57}{space 3}0.000{col 65}{space 4} .0406594{col 78}{space 3} .1129642
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5242259{col 37}{space 2} .0262992{col 48}{space 1}   19.93{col 57}{space 3}0.000{col 65}{space 4} .4726148{col 78}{space 3} .5758369
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}.         
.         foreach x in "militancy" {c -(}
{txt}  2{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' tv tv_treat_`x', cluster(psu_new) 
{txt}  3{com}.                 reg policy_pref_`x' treat_`x' poverty poverty_treat_`x' tv tv_treat_`x' *_z *_miss, cluster(psu_new)
{txt}  4{com}.         {c )-}

{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F(  5,   952) ={res}    1.69
                                                       {txt}Prob > F      = {res} 0.1333
                                                       {txt}R-squared     = {res} 0.0042
                                                       {txt}Root MSE      = {res} .25463

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0504027{col 37}{space 2} .0280702{col 48}{space 1}    1.80{col 57}{space 3}0.073{col 65}{space 4} -.004684{col 78}{space 3} .1054894
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0329585{col 37}{space 2} .0235391{col 48}{space 1}    1.40{col 57}{space 3}0.162{col 65}{space 4} -.013236{col 78}{space 3}  .079153
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0541094{col 37}{space 2} .0286242{col 48}{space 1}   -1.89{col 57}{space 3}0.059{col 65}{space 4}-.1102831{col 78}{space 3} .0020644
{txt}{space 21}tv {c |}{col 25}{res}{space 2} .0468374{col 37}{space 2} .0210533{col 48}{space 1}    2.22{col 57}{space 3}0.026{col 65}{space 4} .0055213{col 78}{space 3} .0881536
{txt}{space 5}tv_treat_militancy {c |}{col 25}{res}{space 2}-.0470203{col 37}{space 2} .0248512{col 48}{space 1}   -1.89{col 57}{space 3}0.059{col 65}{space 4}-.0957897{col 78}{space 3} .0017492
{txt}{space 18}_cons {c |}{col 25}{res}{space 2} .5875882{col 37}{space 2} .0238241{col 48}{space 1}   24.66{col 57}{space 3}0.000{col 65}{space 4} .5408343{col 78}{space 3} .6343421
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}
{txt}Linear regression                                      Number of obs ={res}   10485
                                                       {txt}F( 19,   952) ={res}    7.41
                                                       {txt}Prob > F      = {res} 0.0000
                                                       {txt}R-squared     = {res} 0.0386
                                                       {txt}Root MSE      = {res} .25036

{txt}{ralign 89:(Std. Err. adjusted for {res:953} clusters in psu_new)}
{hline 24}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 25}{c |}{col 37}    Robust
{col 1}  policy_pref_militancy{col 25}{c |}      Coef.{col 37}   Std. Err.{col 49}      t{col 57}   P>|t|{col 65}     [95% Con{col 78}f. Interval]
{hline 24}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 8}treat_militancy {c |}{col 25}{res}{space 2} .0425839{col 37}{space 2} .0271259{col 48}{space 1}    1.57{col 57}{space 3}0.117{col 65}{space 4}-.0106497{col 78}{space 3} .0958174
{txt}{space 16}poverty {c |}{col 25}{res}{space 2} .0240212{col 37}{space 2} .0227243{col 48}{space 1}    1.06{col 57}{space 3}0.291{col 65}{space 4}-.0205743{col 78}{space 3} .0686167
{txt}poverty_treat_militancy {c |}{col 25}{res}{space 2}-.0477981{col 37}{space 2} .0275612{col 48}{space 1}   -1.73{col 57}{space 3}0.083{col 65}{space 4}-.1018858{col 78}{space 3} .0062897
{txt}{space 21}tv {c |}{col 25}{res}{space 2} .0511055{col 37}{space 2}  .021198{col 48}{space 1}    2.41{col 57}{space 3}0.016{col 65}{space 4} .0095053{col 78}{space 3} .0927057
{txt}{space 5}tv_treat_militancy {c |}{col 25}{res}{space 2}-.0487665{col 37}{space 2} .0241165{col 48}{space 1}   -2.02{col 57}{space 3}0.043{col 65}{space 4}-.0960941{col 78}{space 3}-.0014389
{txt}{space 15}gender_z {c |}{col 25}{res}{space 2} .0285133{col 37}{space 2}   .01371{col 48}{space 1}    2.08{col 57}{space 3}0.038{col 65}{space 4}  .001608{col 78}{space 3} .0554185
{txt}{space 16}headh_z {c |}{col 25}{res}{space 2}  -.00524{col 37}{space 2} .0094489{col 48}{space 1}   -0.55{col 57}{space 3}0.579{col 65}{space 4}-.0237831{col 78}{space 3} .0133031
{txt}{space 18}age_z {c |}{col 25}{res}{space 2} .0268482{col 37}{space 2} .0213873{col 48}{space 1}    1.26{col 57}{space 3}0.210{col 65}{space 4}-.0151236{col 78}{space 3}   .06882
{txt}{space 17}read_z {c |}{col 25}{res}{space 2}-.0208087{col 37}{space 2} .0121547{col 48}{space 1}   -1.71{col 57}{space 3}0.087{col 65}{space 4}-.0446619{col 78}{space 3} .0030445
{txt}{space 17}math_z {c |}{col 25}{res}{space 2} .0648866{col 37}{space 2} .0138831{col 48}{space 1}    4.67{col 57}{space 3}0.000{col 65}{space 4} .0376416{col 78}{space 3} .0921315
{txt}{space 17}educ_z {c |}{col 25}{res}{space 2} .0527982{col 37}{space 2}  .019772{col 48}{space 1}    2.67{col 57}{space 3}0.008{col 65}{space 4} .0139964{col 78}{space 3}    .0916
{txt}{space 10}houseexpend_z {c |}{col 25}{res}{space 2} .2384847{col 37}{space 2} .0414909{col 48}{space 1}    5.75{col 57}{space 3}0.000{col 65}{space 4} .1570605{col 78}{space 3} .3199088
{txt}{space 11}assetindex_z {c |}{col 25}{res}{space 2}-.0682095{col 37}{space 2} .0381504{col 48}{space 1}   -1.79{col 57}{space 3}0.074{col 65}{space 4}-.1430782{col 78}{space 3} .0066591
{txt}{space 13}headh_miss {c |}{col 25}{res}{space 2}-.0366144{col 37}{space 2} .0496492{col 48}{space 1}   -0.74{col 57}{space 3}0.461{col 65}{space 4} -.134049{col 78}{space 3} .0608201
{txt}{space 15}age_miss {c |}{col 25}{res}{space 2} .1806731{col 37}{space 2} .0524335{col 48}{space 1}    3.45{col 57}{space 3}0.001{col 65}{space 4} .0777745{col 78}{space 3} .2835717
{txt}{space 14}read_miss {c |}{col 25}{res}{space 2}-.0800548{col 37}{space 2} .0408892{col 48}{space 1}   -1.96{col 57}{space 3}0.051{col 65}{space 4}-.1602981{col 78}{space 3} .0001885
{txt}{space 14}math_miss {c |}{col 25}{res}{space 2} .0865825{col 37}{space 2} .0171376{col 48}{space 1}    5.05{col 57}{space 3}0.000{col 65}{space 4} .0529506{col 78}{space 3} .1202143
{txt}{space 14}educ_miss {c |}{col 25}{res}{space 2} .1225886{col 37}{space 2} .0565524{col 48}{space 1}    2.17{col 57}{space 3}0.030{col 65}{space 4} .0116068{col 78}{space 3} .2335704
{txt}{space 7}houseexpend_miss {c |}{col 25}{res}{space 2}  .077366{col 37}{space 2} .0184131{col 48}{space 1}    4.20{col 57}{space 3}0.000{col 65}{space 4} .0412311{col 78}{space 3} .1135009
{txt}{space 18}_cons {c |}{col 25}{res}{space 2}  .503518{col 37}{space 2}  .028253{col 48}{space 1}   17.82{col 57}{space 3}0.000{col 65}{space 4} .4480726{col 78}{space 3} .5589635
{txt}{hline 24}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{res}{txt}
{com}. 
. 
. *******************************************************
. ****************** APPENDIX FIGURES *******************
. *******************************************************
. 
. // Appendix Figure 1: Balance on the Endorsement Experiment
. 
. destring psu_new, replace
{txt}psu_new has all characters numeric; {res}replaced {txt}as {res}long
{txt}(53 missing values generated)

{com}. 
.         foreach var of varlist gender_z headh_z age_z read_z math_z educ_z houseexpend_z assetindex_z {c -(} //all variables balanced except education
{txt}  2{com}.                 clttest `var', by(control_assign) cluster(psu_new)
{txt}  3{com}.         {c )-}

{txt} t-test adjusted for clustering
{res} gender_z{txt} by {res}control_assign{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.8426
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 control_assign=0{res}{col 11} 12998{col 22}1011{col 28}  0.6118{col 40}  0.0158{txt}{col 55}[{res}  0.5807{txt},{res}  0.6429{txt}]
 control_assign=1{res}{col 11}  3228{col 22}255{col 28}  0.5455{col 40}  0.0319{txt}{col 55}[{res}  0.4828{txt},{res}  0.6083{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}255{col 28}  0.5986{col 40}  0.0142{txt}{col 55}[{res}  0.5708{txt},{res}  0.6264{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res}  0.0662{txt}{col 40}{res}  0.0356{txt}{col 55}[{res} -0.0035{txt},{res}  0.1360{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  1.8621          {txt}      t = {res}  1.8621          {txt}    t = {res}  1.8621
   {txt}P < t = {res}  0.9686          {txt}P > |t| = {res}  0.0628          {txt}P > t = {res}  0.0314

{txt} t-test adjusted for clustering
{res} headh_z{txt} by {res}control_assign{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.3292
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 control_assign=0{res}{col 11} 12998{col 22}1011{col 28}  0.3998{col 40}  0.0104{txt}{col 55}[{res}  0.3793{txt},{res}  0.4202{txt}]
 control_assign=1{res}{col 11}  3228{col 22}255{col 28}  0.3817{col 40}  0.0210{txt}{col 55}[{res}  0.3403{txt},{res}  0.4230{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}255{col 28}  0.3962{col 40}  0.0093{txt}{col 55}[{res}  0.3778{txt},{res}  0.4145{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res}  0.0181{txt}{col 40}{res}  0.0234{txt}{col 55}[{res} -0.0279{txt},{res}  0.0641{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  0.7718          {txt}      t = {res}  0.7718          {txt}    t = {res}  0.7718
   {txt}P < t = {res}  0.7798          {txt}P > |t| = {res}  0.4404          {txt}P > t = {res}  0.2202

{txt} t-test adjusted for clustering
{res} age_z{txt} by {res}control_assign{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.0740
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 control_assign=0{res}{col 11} 12998{col 22}1011{col 28}  0.2459{col 40}  0.0022{txt}{col 55}[{res}  0.2415{txt},{res}  0.2502{txt}]
 control_assign=1{res}{col 11}  3228{col 22}255{col 28}  0.2466{col 40}  0.0045{txt}{col 55}[{res}  0.2377{txt},{res}  0.2554{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}255{col 28}  0.2460{col 40}  0.0020{txt}{col 55}[{res}  0.2421{txt},{res}  0.2499{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0007{txt}{col 40}{res}  0.0050{txt}{col 55}[{res} -0.0105{txt},{res}  0.0091{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.1370          {txt}      t = {res} -0.1370          {txt}    t = {res} -0.1370
   {txt}P < t = {res}  0.4455          {txt}P > |t| = {res}  0.8910          {txt}P > t = {res}  0.5545

{txt} t-test adjusted for clustering
{res} read_z{txt} by {res}control_assign{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2710
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 control_assign=0{res}{col 11} 12998{col 22}1011{col 28}  0.5561{col 40}  0.0098{txt}{col 55}[{res}  0.5369{txt},{res}  0.5753{txt}]
 control_assign=1{res}{col 11}  3228{col 22}255{col 28}  0.5254{col 40}  0.0197{txt}{col 55}[{res}  0.4866{txt},{res}  0.5642{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}255{col 28}  0.5500{col 40}  0.0088{txt}{col 55}[{res}  0.5328{txt},{res}  0.5672{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res}  0.0307{txt}{col 40}{res}  0.0220{txt}{col 55}[{res} -0.0125{txt},{res}  0.0739{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  1.3936          {txt}      t = {res}  1.3936          {txt}    t = {res}  1.3936
   {txt}P < t = {res}  0.9182          {txt}P > |t| = {res}  0.1637          {txt}P > t = {res}  0.0818

{txt} t-test adjusted for clustering
{res} math_z{txt} by {res}control_assign{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2639
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 control_assign=0{res}{col 11} 12998{col 22}1011{col 28}  0.7560{col 40}  0.0084{txt}{col 55}[{res}  0.7395{txt},{res}  0.7726{txt}]
 control_assign=1{res}{col 11}  3228{col 22}255{col 28}  0.7314{col 40}  0.0170{txt}{col 55}[{res}  0.6980{txt},{res}  0.7648{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}255{col 28}  0.7511{col 40}  0.0075{txt}{col 55}[{res}  0.7363{txt},{res}  0.7659{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res}  0.0246{txt}{col 40}{res}  0.0189{txt}{col 55}[{res} -0.0125{txt},{res}  0.0618{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  1.3008          {txt}      t = {res}  1.3008          {txt}    t = {res}  1.3008
   {txt}P < t = {res}  0.9032          {txt}P > |t| = {res}  0.1936          {txt}P > t = {res}  0.0968

{txt} t-test adjusted for clustering
{res} educ_z{txt} by {res}control_assign{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2521
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 control_assign=0{res}{col 11} 12998{col 22}1011{col 28}  0.2852{col 40}  0.0055{txt}{col 55}[{res}  0.2744{txt},{res}  0.2959{txt}]
 control_assign=1{res}{col 11}  3228{col 22}255{col 28}  0.2587{col 40}  0.0110{txt}{col 55}[{res}  0.2370{txt},{res}  0.2804{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}255{col 28}  0.2799{col 40}  0.0049{txt}{col 55}[{res}  0.2703{txt},{res}  0.2895{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res}  0.0265{txt}{col 40}{res}  0.0123{txt}{col 55}[{res}  0.0024{txt},{res}  0.0507{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  2.1556          {txt}      t = {res}  2.1556          {txt}    t = {res}  2.1556
   {txt}P < t = {res}  0.9843          {txt}P > |t| = {res}  0.0313          {txt}P > t = {res}  0.0157

{txt} t-test adjusted for clustering
{res} houseexpend_z{txt} by {res}control_assign{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2615
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 control_assign=0{res}{col 11} 12998{col 22}1011{col 28}  0.1707{col 40}  0.0022{txt}{col 55}[{res}  0.1663{txt},{res}  0.1750{txt}]
 control_assign=1{res}{col 11}  3228{col 22}255{col 28}  0.1673{col 40}  0.0045{txt}{col 55}[{res}  0.1585{txt},{res}  0.1761{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}255{col 28}  0.1700{col 40}  0.0020{txt}{col 55}[{res}  0.1661{txt},{res}  0.1739{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res}  0.0034{txt}{col 40}{res}  0.0050{txt}{col 55}[{res} -0.0064{txt},{res}  0.0131{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  0.6744          {txt}      t = {res}  0.6744          {txt}    t = {res}  0.6744
   {txt}P < t = {res}  0.7499          {txt}P > |t| = {res}  0.5002          {txt}P > t = {res}  0.2501

{txt} t-test adjusted for clustering
{res} assetindex_z{txt} by {res}control_assign{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.4909
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 control_assign=0{res}{col 11} 12998{col 22}1011{col 28}  0.4805{col 40}  0.0041{txt}{col 55}[{res}  0.4725{txt},{res}  0.4885{txt}]
 control_assign=1{res}{col 11}  3228{col 22}255{col 28}  0.4892{col 40}  0.0082{txt}{col 55}[{res}  0.4730{txt},{res}  0.5053{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}255{col 28}  0.4822{col 40}  0.0036{txt}{col 55}[{res}  0.4750{txt},{res}  0.4893{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0087{txt}{col 40}{res}  0.0091{txt}{col 55}[{res} -0.0266{txt},{res}  0.0093{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.9505          {txt}      t = {res} -0.9505          {txt}    t = {res} -0.9505
   {txt}P < t = {res}  0.1710          {txt}P > |t| = {res}  0.3420          {txt}P > t = {res}  0.8290
{txt}
{com}. 
. // Appendix Figure 2: Balance on the Poverty Experiment
. 
.         foreach var of varlist gender_z headh_z age_z read_z math_z educ_z houseexpend_z assetindex_z {c -(} //all variables balanced
{txt}  2{com}.                 clttest `var', by(poverty) cluster(psu_new)
{txt}  3{com}.         {c )-}

{txt} t-test adjusted for clustering
{res} gender_z{txt} by {res}poverty{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.8427
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 poverty=0{res}{col 11}  8128{col 22}640{col 28}  0.5737{col 40}  0.0199{txt}{col 55}[{res}  0.5346{txt},{res}  0.6128{txt}]
 poverty=1{res}{col 11}  8098{col 22}626{col 28}  0.6236{col 40}  0.0202{txt}{col 55}[{res}  0.5840{txt},{res}  0.6633{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}626{col 28}  0.5986{col 40}  0.0142{txt}{col 55}[{res}  0.5708{txt},{res}  0.6264{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0499{txt}{col 40}{res}  0.0284{txt}{col 55}[{res} -0.1056{txt},{res}  0.0057{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -1.7597          {txt}      t = {res} -1.7597          {txt}    t = {res} -1.7597
   {txt}P < t = {res}  0.0393          {txt}P > |t| = {res}  0.0787          {txt}P > t = {res}  0.9607

{txt} t-test adjusted for clustering
{res} headh_z{txt} by {res}poverty{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.3288
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 poverty=0{res}{col 11}  8128{col 22}640{col 28}  0.3816{col 40}  0.0131{txt}{col 55}[{res}  0.3559{txt},{res}  0.4074{txt}]
 poverty=1{res}{col 11}  8098{col 22}626{col 28}  0.4107{col 40}  0.0133{txt}{col 55}[{res}  0.3846{txt},{res}  0.4368{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}626{col 28}  0.3962{col 40}  0.0093{txt}{col 55}[{res}  0.3778{txt},{res}  0.4145{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0291{txt}{col 40}{res}  0.0187{txt}{col 55}[{res} -0.0657{txt},{res}  0.0076{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -1.5570          {txt}      t = {res} -1.5570          {txt}    t = {res} -1.5570
   {txt}P < t = {res}  0.0599          {txt}P > |t| = {res}  0.1197          {txt}P > t = {res}  0.9401

{txt} t-test adjusted for clustering
{res} age_z{txt} by {res}poverty{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.0740
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 poverty=0{res}{col 11}  8128{col 22}640{col 28}  0.2459{col 40}  0.0028{txt}{col 55}[{res}  0.2404{txt},{res}  0.2514{txt}]
 poverty=1{res}{col 11}  8098{col 22}626{col 28}  0.2461{col 40}  0.0028{txt}{col 55}[{res}  0.2405{txt},{res}  0.2517{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}626{col 28}  0.2460{col 40}  0.0020{txt}{col 55}[{res}  0.2421{txt},{res}  0.2499{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0002{txt}{col 40}{res}  0.0040{txt}{col 55}[{res} -0.0080{txt},{res}  0.0077{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.0431          {txt}      t = {res} -0.0431          {txt}    t = {res} -0.0431
   {txt}P < t = {res}  0.4828          {txt}P > |t| = {res}  0.9656          {txt}P > t = {res}  0.5172

{txt} t-test adjusted for clustering
{res} read_z{txt} by {res}poverty{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2714
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 poverty=0{res}{col 11}  8128{col 22}640{col 28}  0.5476{col 40}  0.0124{txt}{col 55}[{res}  0.5234{txt},{res}  0.5719{txt}]
 poverty=1{res}{col 11}  8098{col 22}626{col 28}  0.5524{col 40}  0.0125{txt}{col 55}[{res}  0.5278{txt},{res}  0.5769{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}626{col 28}  0.5500{col 40}  0.0088{txt}{col 55}[{res}  0.5327{txt},{res}  0.5672{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0047{txt}{col 40}{res}  0.0176{txt}{col 55}[{res} -0.0392{txt},{res}  0.0297{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.2701          {txt}      t = {res} -0.2701          {txt}    t = {res} -0.2701
   {txt}P < t = {res}  0.3936          {txt}P > |t| = {res}  0.7871          {txt}P > t = {res}  0.6064

{txt} t-test adjusted for clustering
{res} math_z{txt} by {res}poverty{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2641
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 poverty=0{res}{col 11}  8128{col 22}640{col 28}  0.7452{col 40}  0.0106{txt}{col 55}[{res}  0.7244{txt},{res}  0.7660{txt}]
 poverty=1{res}{col 11}  8098{col 22}626{col 28}  0.7571{col 40}  0.0107{txt}{col 55}[{res}  0.7360{txt},{res}  0.7782{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}626{col 28}  0.7511{col 40}  0.0076{txt}{col 55}[{res}  0.7363{txt},{res}  0.7660{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0119{txt}{col 40}{res}  0.0151{txt}{col 55}[{res} -0.0415{txt},{res}  0.0177{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.7878          {txt}      t = {res} -0.7878          {txt}    t = {res} -0.7878
   {txt}P < t = {res}  0.2155          {txt}P > |t| = {res}  0.4309          {txt}P > t = {res}  0.7845

{txt} t-test adjusted for clustering
{res} educ_z{txt} by {res}poverty{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2531
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 poverty=0{res}{col 11}  8128{col 22}640{col 28}  0.2789{col 40}  0.0069{txt}{col 55}[{res}  0.2653{txt},{res}  0.2925{txt}]
 poverty=1{res}{col 11}  8098{col 22}626{col 28}  0.2809{col 40}  0.0070{txt}{col 55}[{res}  0.2672{txt},{res}  0.2947{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}626{col 28}  0.2799{col 40}  0.0049{txt}{col 55}[{res}  0.2703{txt},{res}  0.2896{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0020{txt}{col 40}{res}  0.0098{txt}{col 55}[{res} -0.0213{txt},{res}  0.0173{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.2055          {txt}      t = {res} -0.2055          {txt}    t = {res} -0.2055
   {txt}P < t = {res}  0.4186          {txt}P > |t| = {res}  0.8372          {txt}P > t = {res}  0.5814

{txt} t-test adjusted for clustering
{res} houseexpend_z{txt} by {res}poverty{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2615
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 poverty=0{res}{col 11}  8128{col 22}640{col 28}  0.1686{col 40}  0.0028{txt}{col 55}[{res}  0.1631{txt},{res}  0.1741{txt}]
 poverty=1{res}{col 11}  8098{col 22}626{col 28}  0.1714{col 40}  0.0028{txt}{col 55}[{res}  0.1659{txt},{res}  0.1770{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}626{col 28}  0.1700{col 40}  0.0020{txt}{col 55}[{res}  0.1661{txt},{res}  0.1739{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0029{txt}{col 40}{res}  0.0040{txt}{col 55}[{res} -0.0107{txt},{res}  0.0049{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.7229          {txt}      t = {res} -0.7229          {txt}    t = {res} -0.7229
   {txt}P < t = {res}  0.2349          {txt}P > |t| = {res}  0.4699          {txt}P > t = {res}  0.7651

{txt} t-test adjusted for clustering
{res} assetindex_z{txt} by {res}poverty{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.4909
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 poverty=0{res}{col 11}  8128{col 22}640{col 28}  0.4792{col 40}  0.0051{txt}{col 55}[{res}  0.4691{txt},{res}  0.4892{txt}]
 poverty=1{res}{col 11}  8098{col 22}626{col 28}  0.4852{col 40}  0.0052{txt}{col 55}[{res}  0.4751{txt},{res}  0.4954{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11} 16226{col 22}626{col 28}  0.4822{col 40}  0.0036{txt}{col 55}[{res}  0.4750{txt},{res}  0.4893{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11} 16226{col 22}1266{txt}{col 28}{res} -0.0061{txt}{col 40}{res}  0.0073{txt}{col 55}[{res} -0.0204{txt},{res}  0.0082{txt}]

 Degrees freedom:    {res}1264

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.8351          {txt}      t = {res} -0.8351          {txt}    t = {res} -0.8351
   {txt}P < t = {res}  0.2019          {txt}P > |t| = {res}  0.4038          {txt}P > t = {res}  0.7981
{txt}
{com}. 
. // Appendix Figure 3: Balance on the Violence Experiment
. 
.         foreach var of varlist gender_z headh_z age_z read_z math_z educ_z houseexpend_z assetindex_z {c -(} //all variables balanced
{txt}  2{com}.                 clttest `var', by(natviol) cluster(psu_new)
{txt}  3{com}.         {c )-}

{txt} t-test adjusted for clustering
{res} gender_z{txt} by {res}natviol{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.8550
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 natviol=0{res}{col 11}  4059{col 22}317{col 28}  0.5928{col 40}  0.0284{txt}{col 55}[{res}  0.5368{txt},{res}  0.6487{txt}]
 natviol=1{res}{col 11}  4056{col 22}324{col 28}  0.5759{col 40}  0.0287{txt}{col 55}[{res}  0.5195{txt},{res}  0.6324{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11}  8115{col 22}324{col 28}  0.5843{col 40}  0.0202{txt}{col 55}[{res}  0.5447{txt},{res}  0.6240{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11}  8115{col 22}641{txt}{col 28}{res}  0.0168{txt}{col 40}{res}  0.0404{txt}{col 55}[{res} -0.0625{txt},{res}  0.0961{txt}]

 Degrees freedom:    {res}639

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  0.4164          {txt}      t = {res}  0.4164          {txt}    t = {res}  0.4164
   {txt}P < t = {res}  0.6614          {txt}P > |t| = {res}  0.6773          {txt}P > t = {res}  0.3386

{txt} t-test adjusted for clustering
{res} headh_z{txt} by {res}natviol{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.3391
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 natviol=0{res}{col 11}  4059{col 22}317{col 28}  0.3885{col 40}  0.0186{txt}{col 55}[{res}  0.3518{txt},{res}  0.4252{txt}]
 natviol=1{res}{col 11}  4056{col 22}324{col 28}  0.3814{col 40}  0.0188{txt}{col 55}[{res}  0.3444{txt},{res}  0.4184{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11}  8115{col 22}324{col 28}  0.3850{col 40}  0.0132{txt}{col 55}[{res}  0.3590{txt},{res}  0.4110{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11}  8115{col 22}641{txt}{col 28}{res}  0.0071{txt}{col 40}{res}  0.0265{txt}{col 55}[{res} -0.0449{txt},{res}  0.0591{txt}]

 Degrees freedom:    {res}639

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  0.2686          {txt}      t = {res}  0.2686          {txt}    t = {res}  0.2686
   {txt}P < t = {res}  0.6058          {txt}P > |t| = {res}  0.7883          {txt}P > t = {res}  0.3942

{txt} t-test adjusted for clustering
{res} age_z{txt} by {res}natviol{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.0786
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 natviol=0{res}{col 11}  4059{col 22}317{col 28}  0.2454{col 40}  0.0040{txt}{col 55}[{res}  0.2375{txt},{res}  0.2534{txt}]
 natviol=1{res}{col 11}  4056{col 22}324{col 28}  0.2492{col 40}  0.0041{txt}{col 55}[{res}  0.2412{txt},{res}  0.2572{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11}  8115{col 22}324{col 28}  0.2473{col 40}  0.0029{txt}{col 55}[{res}  0.2417{txt},{res}  0.2530{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11}  8115{col 22}641{txt}{col 28}{res} -0.0038{txt}{col 40}{res}  0.0057{txt}{col 55}[{res} -0.0151{txt},{res}  0.0074{txt}]

 Degrees freedom:    {res}639

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res} -0.6648          {txt}      t = {res} -0.6648          {txt}    t = {res} -0.6648
   {txt}P < t = {res}  0.2532          {txt}P > |t| = {res}  0.5064          {txt}P > t = {res}  0.7468

{txt} t-test adjusted for clustering
{res} read_z{txt} by {res}natviol{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2519
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 natviol=0{res}{col 11}  4059{col 22}317{col 28}  0.5499{col 40}  0.0169{txt}{col 55}[{res}  0.5166{txt},{res}  0.5832{txt}]
 natviol=1{res}{col 11}  4056{col 22}324{col 28}  0.5271{col 40}  0.0171{txt}{col 55}[{res}  0.4936{txt},{res}  0.5607{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11}  8115{col 22}324{col 28}  0.5385{col 40}  0.0120{txt}{col 55}[{res}  0.5149{txt},{res}  0.5621{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11}  8115{col 22}641{txt}{col 28}{res}  0.0228{txt}{col 40}{res}  0.0240{txt}{col 55}[{res} -0.0244{txt},{res}  0.0699{txt}]

 Degrees freedom:    {res}639

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  0.9477          {txt}      t = {res}  0.9477          {txt}    t = {res}  0.9477
   {txt}P < t = {res}  0.8282          {txt}P > |t| = {res}  0.3436          {txt}P > t = {res}  0.1718

{txt} t-test adjusted for clustering
{res} math_z{txt} by {res}natviol{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2675
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 natviol=0{res}{col 11}  4059{col 22}317{col 28}  0.7492{col 40}  0.0151{txt}{col 55}[{res}  0.7195{txt},{res}  0.7789{txt}]
 natviol=1{res}{col 11}  4056{col 22}324{col 28}  0.7478{col 40}  0.0152{txt}{col 55}[{res}  0.7179{txt},{res}  0.7777{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11}  8115{col 22}324{col 28}  0.7485{col 40}  0.0107{txt}{col 55}[{res}  0.7275{txt},{res}  0.7695{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11}  8115{col 22}641{txt}{col 28}{res}  0.0014{txt}{col 40}{res}  0.0214{txt}{col 55}[{res} -0.0406{txt},{res}  0.0435{txt}]

 Degrees freedom:    {res}639

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  0.0662          {txt}      t = {res}  0.0662          {txt}    t = {res}  0.0662
   {txt}P < t = {res}  0.5264          {txt}P > |t| = {res}  0.9472          {txt}P > t = {res}  0.4736

{txt} t-test adjusted for clustering
{res} educ_z{txt} by {res}natviol{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2357
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 natviol=0{res}{col 11}  4059{col 22}317{col 28}  0.2842{col 40}  0.0095{txt}{col 55}[{res}  0.2656{txt},{res}  0.3029{txt}]
 natviol=1{res}{col 11}  4056{col 22}324{col 28}  0.2581{col 40}  0.0095{txt}{col 55}[{res}  0.2393{txt},{res}  0.2769{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11}  8115{col 22}324{col 28}  0.2712{col 40}  0.0067{txt}{col 55}[{res}  0.2580{txt},{res}  0.2844{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11}  8115{col 22}641{txt}{col 28}{res}  0.0261{txt}{col 40}{res}  0.0135{txt}{col 55}[{res} -0.0003{txt},{res}  0.0525{txt}]

 Degrees freedom:    {res}639

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  1.9426          {txt}      t = {res}  1.9426          {txt}    t = {res}  1.9426
   {txt}P < t = {res}  0.9738          {txt}P > |t| = {res}  0.0525          {txt}P > t = {res}  0.0262

{txt} t-test adjusted for clustering
{res} houseexpend_z{txt} by {res}natviol{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.2515
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 natviol=0{res}{col 11}  4059{col 22}317{col 28}  0.1734{col 40}  0.0038{txt}{col 55}[{res}  0.1659{txt},{res}  0.1810{txt}]
 natviol=1{res}{col 11}  4056{col 22}324{col 28}  0.1679{col 40}  0.0039{txt}{col 55}[{res}  0.1603{txt},{res}  0.1755{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11}  8115{col 22}324{col 28}  0.1707{col 40}  0.0027{txt}{col 55}[{res}  0.1654{txt},{res}  0.1760{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11}  8115{col 22}641{txt}{col 28}{res}  0.0055{txt}{col 40}{res}  0.0054{txt}{col 55}[{res} -0.0052{txt},{res}  0.0162{txt}]

 Degrees freedom:    {res}639

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  1.0147          {txt}      t = {res}  1.0147          {txt}    t = {res}  1.0147
   {txt}P < t = {res}  0.8447          {txt}P > |t| = {res}  0.3106          {txt}P > t = {res}  0.1553

{txt} t-test adjusted for clustering
{res} assetindex_z{txt} by {res}natviol{txt}, clustered by {res}psu_new
{txt} ------------------------------------------------------------------------
  Intra-cluster correlation{col 37}= {res}          0.4895
{txt} ------------------------------------------------------------------------
{col 15}N    Clusts    Mean           SE{col 60}95 % CI
 natviol=0{res}{col 11}  4059{col 22}317{col 28}  0.4844{col 40}  0.0071{txt}{col 55}[{res}  0.4704{txt},{res}  0.4983{txt}]
 natviol=1{res}{col 11}  4056{col 22}324{col 28}  0.4840{col 40}  0.0072{txt}{col 55}[{res}  0.4700{txt},{res}  0.4981{txt}]
 ------------------------------------------------------------------------
 Combined {res}{col 11}  8115{col 22}324{col 28}  0.4842{col 40}  0.0050{txt}{col 55}[{res}  0.4743{txt},{res}  0.4941{txt}]
 ------------------------------------------------------------------------
 Diff(0-1){res}{col 11}  8115{col 22}641{txt}{col 28}{res}  0.0003{txt}{col 40}{res}  0.0101{txt}{col 55}[{res} -0.0195{txt},{res}  0.0201{txt}]

 Degrees freedom:    {res}639

{txt}                    Ho: mean(-) = mean(diff) = 0

  Ha: mean(diff) < 0         Ha: mean(diff) ~= 0        Ha: mean(diff) > 0
       t = {res}  0.0324          {txt}      t = {res}  0.0324          {txt}    t = {res}  0.0324
   {txt}P < t = {res}  0.5129          {txt}P > |t| = {res}  0.9742          {txt}P > t = {res}  0.4871
{txt}
{com}.         
. // Appendix Figure 5: Balance on the Violence Experiment
. 
.         tab k_scale

    {txt}k_scale {c |}      Freq.     Percent        Cum.
{hline 12}{c +}{hline 35}
          0 {c |}{res}      3,880       23.83       23.83
{txt}        .25 {c |}{res}      2,533       15.56       39.39
{txt}         .5 {c |}{res}      3,467       21.30       60.69
{txt}        .75 {c |}{res}      2,774       17.04       77.73
{txt}          1 {c |}{res}      3,625       22.27      100.00
{txt}{hline 12}{c +}{hline 35}
      Total {c |}{res}     16,279      100.00
{txt}
{com}. 
{txt}end of do-file

{com}. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/rebeccalittman/Documents/PK2 share/Replication/Data/ReplicationResults.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res}17 Dec 2015, 10:45:27
{txt}{.-}
{smcl}
{txt}{sf}{ul off}